From a84c2be40bb886f214480d2560b76283387c70bf Mon Sep 17 00:00:00 2001
From: Emre Sahin <galaxy@emresult.com>
Date: Fri, 2 Jul 2021 14:27:46 +0300
Subject: [PATCH 01/89] experiments draft 1 moved to experiments-trail/

---
 .../start/experiments-trail/experiments-1.md  | 215 ++++++++++++++++++
 1 file changed, 215 insertions(+)
 create mode 100644 content/docs/start/experiments-trail/experiments-1.md

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
new file mode 100644
index 0000000000..a6a5d5aa79
--- /dev/null
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -0,0 +1,215 @@
+---
+title: 'Get Started: Experiments'
+---
+
+# Get Started with Experiments
+
+<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
+parameters to tune or other permutations of the code. We can organize such
+projects and keep only what we ultimately need with `dvc experiments`. DVC can
+track experiments for you so there's no need to commit each one to Git. This way
+your repo doesn't become polluted with all of them. You can discard experiments
+once they're no longer needed.
+
+Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
+[compare the changes](/doc/start/metrics-parameters-plots). Let's further
+increase the number of features in the `featurize` stage to see how it compares.
+<details>
+## Installing and Configuring the Project
+
+These commands are run in the
+[`get-started-experiments`](https://github.com/iterative/get-started-experiments)
+project. You can run the commands in this document after cloning the repository
+and installing the requirements.
+
+### Clone the project and create venv
+
+Please clone the project and create a virtual environment. 
+
+> We create a virtual environment to keep the libraries we use isolated from
+> the rest of your system. This prevents version conflicts.
+
+```dvc
+$ git clone https://github.com/iterative/get-started-experiments -b git-init
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
+```
+
+### Create the pipeline
+
+DVC tracks the dependencies across project elements with pipelines. Experiments
+also need a pipeline to run.  
+
+We create a two stage pipeline to expand the dataset from a `tar.gz` file
+to a directory and specify the training command to depend on dataset and a
+parameter, and produce a metrics file.
+
+```dvc
+$ dvc stage add -n expand \
+                -d data/fashion-mnist.tar.gz \
+                -o data/images \
+                tar xvzf data/fashion-mnist.tar.gz
+$ dvc stage add -n train \
+                -p conv_units \
+                -d data/images \
+                -m metrics.json \
+                python3 train.py 
+```
+
+### Get the data set
+
+The repository you cloned doesn't contain the dataset. DVC tracks the datafiles
+separately from the text files.  In order to get `fashion-mnist.tar.gz` from
+the `dataset-registry`, we ask DVC to pull the missing data files. 
+
+```dvc
+$ dvc pull
+```
+
+</details> ## Running experiments ### Running with default parameters
+
+The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+experiments. By _ephemeral_ we mean the experiments can be run without
+committing parameter and dependency changes to Git. Instead the artifacts
+produced for each experiment is tracked by DVC and persisted on demand. 
+
+Running the pipeline with default values requires only the command:
+
+``` dvc
+$ dvc exp run
+TK
+```
+
+It runs the pipeline starting from the basic dependencies and produces
+`metrics.json` file for the default state. 
+
+<details>
+
+### If you used `dvc repro` before
+
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may be used to `dvc repro`.
+
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the pipeline.
+
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace.
+It doesn't use any special objects to track the experiments.
+	 
+When you have large number of experiments that you don't want to commit into
+Git, it's better to use `dvc exp run`. It allows to change the parameters
+quickly, can track the history of artifacts and has facilities to compare
+these experiments easily.
+
+`dvc repro` is still available to run the pipeline that don't need these extra
+features. 
+ 
+</details>
+
+### Running by setting parameters
+
+Now let's do some more experimentation. 
+
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
+
+```dvc
+$ dvc exp run --set-param conv_units=24 
+TK
+```
+
+Note that the pipeline didn't run the earliest stage. Only the stages that
+depend on the updated parameter and subsequent stages are run. 
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file.
+We can see the effect of it by looking at the diff. 
+
+```dvc
+$ git diff params.yaml
+TK
+```
+
+### Run multiple experiments in parallel
+
+Instead of running the experiments one-by-one, we can define them first to run
+them in a batch. This is especially handy when you have long running
+experiments. 
+
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter. 
+
+``` dvc
+$ dvc exp run --queue -S conv_units=32
+$ dvc exp run --queue -S conv_units=64
+$ dvc exp run --queue -S conv_units=128
+$ dvc exp run --queue -S conv_units=256
+```
+
+Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+
+```dvc
+$ dvc exp run --run-all --jobs 2
+TK
+```
+
+## Comparing experiments
+
+The pipeline is run several times with different parameters. To compare all of
+these experiments, we use `dvc exp show`. This command presents the parameters
+and metrics produced in experiments in a nicely formatted table.
+
+```dvc
+$ dvc exp show
+```
+TK
+
+By default it shows all the parameters and the metrics along with the
+timestamp. If you have large number of parameters, metrics or experiments, this
+may lead to a cluttered view. You can limit the table to specific metrics, or
+parameters, or hide the timestamp column with `--include-metrics`,
+`--include-params`, or `--no-timestamp` options of the command, respectively.
+
+```dvc
+$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
+TK
+```
+
+## Persisting experiments
+
+After selecting a experiments from the table, you can commit the
+hyperparameters and other dependencies that produced this successful experiment
+to your Git history. 
+
+`dvc exp apply` brings back all specific artifacts and parameters from the
+experiment to the <abbr>workspace</abbr>.
+
+```dvc
+$ dvc exp apply 
+TK
+```
+
+We can see the changes in the repository and commit them to Git. 
+
+```dvc
+$ git diff
+$ git add .
+$ git commit -m "Successful experiment"
+```
+
+## Go Further
+
+You can continue to experiment with [the
+project](https://github.com/iterative/get-started-experiments).  Please see the
+`README.md` file of the project for these. Don't forget to [notify
+us](https://dvc.org/chat) if you happen to find good parameters.
+
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
+
+Please see the section on [Experiment
+Management](/doc/user-guide/experiment-management) in the User's Guide or `dvc
+exp` and subcommands in the Command Reference. 

From 81c4052becd21bbea69f6c3bb94d9efe640c1ba1 Mon Sep 17 00:00:00 2001
From: Emre Sahin <galaxy@emresult.com>
Date: Fri, 2 Jul 2021 16:04:30 +0300
Subject: [PATCH 02/89] modifications for downloading the data and setting up
 the experiment manually

---
 .../start/experiments-trail/experiments-1.md  | 73 +++++++++++++------
 1 file changed, 51 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index a6a5d5aa79..c7ae612e28 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -14,13 +14,18 @@ once they're no longer needed.
 Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
 [compare the changes](/doc/start/metrics-parameters-plots). Let's further
 increase the number of features in the `featurize` stage to see how it compares.
+
+In this section, we will explore the basic features of DVC experiment
+management with `[get-started-experiments]` project. 
+
+get-started-experiments: https://github.com/iterative/get-started-experiments
+
 <details>
 ## Installing and Configuring the Project
 
-These commands are run in the
-[`get-started-experiments`](https://github.com/iterative/get-started-experiments)
-project. You can run the commands in this document after cloning the repository
-and installing the requirements.
+These commands are run in the `[get-started-experiments]` project. You can run
+the commands in this document after cloning the repository and installing the
+requirements.
 
 ### Clone the project and create venv
 
@@ -30,45 +35,69 @@ Please clone the project and create a virtual environment.
 > the rest of your system. This prevents version conflicts.
 
 ```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b git-init
+$ git clone https://github.com/iterative/get-started-experiments -b source-code
 $ cd get-started-experiments
 $ virtualenv .venv
 $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### Create the pipeline
+### Get the data set
+
+The repository you cloned doesn't contain the dataset. In order to get
+`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to
+download the missing data files.  `dvc get` is similar to `wget` but works with
+Git+DVC repositories to download binary files.
+
+```dvc
+$ dvc get https://github.com/iterative/dataset-registry \
+          fashion-mnist/images.tar.gz -o data/images.tar.gz
+```
+
+Then we extract this file that contains labeled images. 
+
+```dvc
+$ tar -xvzf data/images.tar.gz --directory data/
+``` 
+
+### Specifying the experiment
+
+We first initialize DVC inside the project to create an experiment.
+
+```dvc
+$ dvc init
+```
 
-DVC tracks the dependencies across project elements with pipelines. Experiments
-also need a pipeline to run.  
+DVC experiments are run by specifying their commands, outputs, parameters and
+dependencies. We add an experiment command by `dvc stage add`. 
 
-We create a two stage pipeline to expand the dataset from a `tar.gz` file
-to a directory and specify the training command to depend on dataset and a
-parameter, and produce a metrics file.
 
 ```dvc
-$ dvc stage add -n expand \
-                -d data/fashion-mnist.tar.gz \
-                -o data/images \
-                tar xvzf data/fashion-mnist.tar.gz
 $ dvc stage add -n train \
-                -p conv_units \
+                -p model.conv_units \
+                -p train.conv_units \
                 -d data/images \
                 -m metrics.json \
                 python3 train.py 
 ```
 
-### Get the data set
+The command tells DVC to create an experiment named `train`, with two
+parameters and a data dependency to `data/images`. The command produces
+`metrics.json` as a special type of output. 
 
-The repository you cloned doesn't contain the dataset. DVC tracks the datafiles
-separately from the text files.  In order to get `fashion-mnist.tar.gz` from
-the `dataset-registry`, we ask DVC to pull the missing data files. 
+DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
+artifacts. 
 
 ```dvc
-$ dvc pull
+$ git add dvc.yaml .gitignore
+$ git commit -m "added data and the experiment" 
 ```
 
-</details> ## Running experiments ### Running with default parameters
+</details>
+
+## Running experiments 
+
+### Running with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without

From e80af130a6c56f309fe058d0d5e013380001e644 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Sat, 3 Jul 2021 13:46:14 +0300
Subject: [PATCH 03/89] Fix project installation and commands

---
 .../start/experiments-trail/experiments-1.md  | 117 +++++++++---------
 1 file changed, 58 insertions(+), 59 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index c7ae612e28..08f7a9e7fb 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -15,8 +15,8 @@ Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
 [compare the changes](/doc/start/metrics-parameters-plots). Let's further
 increase the number of features in the `featurize` stage to see how it compares.
 
-In this section, we will explore the basic features of DVC experiment
-management with `[get-started-experiments]` project. 
+In this section, we will explore the basic features of DVC experiment management
+with `[get-started-experiments]` project.
 
 get-started-experiments: https://github.com/iterative/get-started-experiments
 
@@ -27,12 +27,12 @@ These commands are run in the `[get-started-experiments]` project. You can run
 the commands in this document after cloning the repository and installing the
 requirements.
 
-### Clone the project and create venv
+### Clone the project and create virtual environment
 
-Please clone the project and create a virtual environment. 
+Please clone the project and create a virtual environment.
 
-> We create a virtual environment to keep the libraries we use isolated from
-> the rest of your system. This prevents version conflicts.
+> We create a virtual environment to keep the libraries we use isolated from the
+> rest of your system. This prevents version conflicts.
 
 ```dvc
 $ git clone https://github.com/iterative/get-started-experiments -b source-code
@@ -45,20 +45,20 @@ $ python -m pip install -r requirements.txt
 ### Get the data set
 
 The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to
-download the missing data files.  `dvc get` is similar to `wget` but works with
-Git+DVC repositories to download binary files.
+`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to download
+the missing data files. `dvc get` is similar to `wget` but works with Git+DVC
+repositories to download binary files.
 
 ```dvc
 $ dvc get https://github.com/iterative/dataset-registry \
           fashion-mnist/images.tar.gz -o data/images.tar.gz
 ```
 
-Then we extract this file that contains labeled images. 
+Then we extract this file that contains labeled images.
 
 ```dvc
 $ tar -xvzf data/images.tar.gz --directory data/
-``` 
+```
 
 ### Specifying the experiment
 
@@ -69,50 +69,49 @@ $ dvc init
 ```
 
 DVC experiments are run by specifying their commands, outputs, parameters and
-dependencies. We add an experiment command by `dvc stage add`. 
-
+dependencies. We add an experiment command by `dvc stage add`.
 
 ```dvc
 $ dvc stage add -n train \
                 -p model.conv_units \
-                -p train.conv_units \
+                -p train.epochs \
                 -d data/images \
                 -m metrics.json \
-                python3 train.py 
+                python3 src/train.py
 ```
 
-The command tells DVC to create an experiment named `train`, with two
-parameters and a data dependency to `data/images`. The command produces
-`metrics.json` as a special type of output. 
+The command tells DVC to create an experiment named `train`, with two parameters
+and a data dependency to `data/images`. The command produces `metrics.json` as a
+special type of output.
 
 DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
-artifacts. 
+artifacts.
 
 ```dvc
 $ git add dvc.yaml .gitignore
-$ git commit -m "added data and the experiment" 
+$ git commit -m "added data and the experiment"
 ```
 
 </details>
 
-## Running experiments 
+## Running experiments
 
 ### Running with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment is tracked by DVC and persisted on demand. 
+produced for each experiment is tracked by DVC and persisted on demand.
 
 Running the pipeline with default values requires only the command:
 
-``` dvc
+```dvc
 $ dvc exp run
 TK
 ```
 
 It runs the pipeline starting from the basic dependencies and produces
-`metrics.json` file for the default state. 
+`metrics.json` file for the default state.
 
 <details>
 
@@ -121,40 +120,39 @@ It runs the pipeline starting from the basic dependencies and produces
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may be used to `dvc repro`.
 
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the pipeline.
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
+pipeline.
 
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace.
-It doesn't use any special objects to track the experiments.
-	 
-When you have large number of experiments that you don't want to commit into
-Git, it's better to use `dvc exp run`. It allows to change the parameters
-quickly, can track the history of artifacts and has facilities to compare
-these experiments easily.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments. When you have large
+number of experiments that you don't want to commit into Git, it's better to use
+`dvc exp run`. It allows to change the parameters quickly, can track the history
+of artifacts and has facilities to compare these experiments easily.
 
 `dvc repro` is still available to run the pipeline that don't need these extra
-features. 
- 
+features.
+
 </details>
 
 ### Running by setting parameters
 
-Now let's do some more experimentation. 
+Now let's do some more experimentation.
 
 DVC allows to update the parameters defined in the pipeline without modifying
 the files manually. We use this feature to set the convolutional units in
 `train.py`.
 
 ```dvc
-$ dvc exp run --set-param conv_units=24 
+$ dvc exp run --set-param conv_units=24
 TK
 ```
 
 Note that the pipeline didn't run the earliest stage. Only the stages that
-depend on the updated parameter and subsequent stages are run. 
+depend on the updated parameter and subsequent stages are run.
 
-When you run `dvc exp run` with `--set-param`, it updates the parameter file.
-We can see the effect of it by looking at the diff. 
+When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
+can see the effect of it by looking at the diff.
 
 ```dvc
 $ git diff params.yaml
@@ -165,12 +163,12 @@ TK
 
 Instead of running the experiments one-by-one, we can define them first to run
 them in a batch. This is especially handy when you have long running
-experiments. 
+experiments.
 
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter. 
+also use `-S` (`--set-param`) to set a value for the parameter.
 
-``` dvc
+```dvc
 $ dvc exp run --queue -S conv_units=32
 $ dvc exp run --queue -S conv_units=64
 $ dvc exp run --queue -S conv_units=128
@@ -193,13 +191,14 @@ and metrics produced in experiments in a nicely formatted table.
 ```dvc
 $ dvc exp show
 ```
+
 TK
 
-By default it shows all the parameters and the metrics along with the
-timestamp. If you have large number of parameters, metrics or experiments, this
-may lead to a cluttered view. You can limit the table to specific metrics, or
-parameters, or hide the timestamp column with `--include-metrics`,
-`--include-params`, or `--no-timestamp` options of the command, respectively.
+By default it shows all the parameters and the metrics along with the timestamp.
+If you have large number of parameters, metrics or experiments, this may lead to
+a cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
 
 ```dvc
 $ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
@@ -208,19 +207,19 @@ TK
 
 ## Persisting experiments
 
-After selecting a experiments from the table, you can commit the
-hyperparameters and other dependencies that produced this successful experiment
-to your Git history. 
+After selecting a experiments from the table, you can commit the hyperparameters
+and other dependencies that produced this successful experiment to your Git
+history.
 
 `dvc exp apply` brings back all specific artifacts and parameters from the
 experiment to the <abbr>workspace</abbr>.
 
 ```dvc
-$ dvc exp apply 
+$ dvc exp apply
 TK
 ```
 
-We can see the changes in the repository and commit them to Git. 
+We can see the changes in the repository and commit them to Git.
 
 ```dvc
 $ git diff
@@ -230,15 +229,15 @@ $ git commit -m "Successful experiment"
 
 ## Go Further
 
-You can continue to experiment with [the
-project](https://github.com/iterative/get-started-experiments).  Please see the
-`README.md` file of the project for these. Don't forget to [notify
-us](https://dvc.org/chat) if you happen to find good parameters.
+You can continue to experiment with
+[the project](https://github.com/iterative/get-started-experiments). Please see
+the `README.md` file of the project for these. Don't forget to
+[notify us](https://dvc.org/chat) if you happen to find good parameters.
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences
 between two experiments.
 
-Please see the section on [Experiment
-Management](/doc/user-guide/experiment-management) in the User's Guide or `dvc
-exp` and subcommands in the Command Reference. 
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From bb56fb72f1252a4ec37e8bb04352768d07a8abbd Mon Sep 17 00:00:00 2001
From: Emre Sahin <iex@redmi.emresahin.net>
Date: Mon, 5 Jul 2021 22:36:14 +0300
Subject: [PATCH 04/89] added second draft for experiments

---
 .../start/experiments-trail/experiments-2.md  | 228 ++++++++++++++++++
 1 file changed, 228 insertions(+)
 create mode 100644 content/docs/start/experiments-trail/experiments-2.md

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
new file mode 100644
index 0000000000..93d9250740
--- /dev/null
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -0,0 +1,228 @@
+---
+title: 'Get Started: Experiments'
+---
+
+# Get Started with Experiments
+
+<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
+parameters to tune or other permutations of the code. We can organize such
+projects and keep only what we ultimately need with `dvc experiments`. DVC can
+track experiments for you so there's no need to commit each one to Git. This way
+your repo doesn't become polluted with all of them. You can discard experiments
+once they're no longer needed.
+
+Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
+[compare the changes](/doc/start/metrics-parameters-plots). Let's further
+increase the number of features in the `featurize` stage to see how it compares.
+
+In this section, we will explore the basic features of DVC experiment management
+with `[get-started-experiments]` project.
+
+get-started-experiments: https://github.com/iterative/get-started-experiments
+
+## Installing and Configuring the Project
+
+These commands are run in the `[get-started-experiments]` project. You can run
+the commands in this document after cloning the repository and installing the
+requirements.
+
+### Clone the project and create virtual environment
+
+Please clone the project and create a virtual environment.
+
+> We create a virtual environment to keep the libraries we use isolated from the
+> rest of your system. This prevents version conflicts.
+
+```dvc
+$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
+```
+
+### Get the data set
+
+The repository you cloned doesn't contain the dataset. In order to get
+`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc pull` to update
+the missing data files. `dvc pull` is used in DVC repositories to update the missing data dependencies. 
+
+```dvc
+$ dvc pull
+```
+
+Then we extract this file that contains labeled images.
+
+```dvc
+$ tar -xvzf data/images.tar.gz --directory data/
+```
+
+</details>
+
+## Running experiments
+
+### Running with default parameters
+
+The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+experiments. By _ephemeral_ we mean the experiments can be run without
+committing parameter and dependency changes to Git. Instead the artifacts
+produced for each experiment is tracked by DVC and persisted on demand.
+
+Running the pipeline with default values requires only the command:
+
+```dvc
+$ dvc exp run
+TK
+```
+
+It runs the pipeline starting from the basic dependencies and produces
+`metrics.json` file for the default state.
+
+<details>
+
+### If you used `dvc repro` before
+
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may be used to `dvc repro`.
+
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
+pipeline.
+
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments. When you have large
+number of experiments that you don't want to commit into Git, it's better to use
+`dvc exp run`. It allows to change the parameters quickly, can track the history
+of artifacts and has facilities to compare these experiments easily.
+
+`dvc repro` is still available to run the pipeline that don't need these extra
+features.
+
+</details>
+
+### Running by setting parameters
+
+Now let's do some more experimentation.
+
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
+
+```dvc
+$ dvc exp run --set-param conv_units=24
+TK
+```
+
+Note that the pipeline didn't run the earliest stage. Only the stages that
+depend on the updated parameter and subsequent stages are run.
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
+can see the effect of it by looking at the diff.
+
+```dvc
+$ git diff params.yaml
+TK
+```
+
+### Run multiple experiments in parallel
+
+Instead of running the experiments one-by-one, we can define them first to run
+them in a batch. This is especially handy when you have long running
+experiments.
+
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter.
+
+```dvc
+$ dvc exp run --queue -S conv_units=32
+$ dvc exp run --queue -S conv_units=64
+$ dvc exp run --queue -S conv_units=128
+$ dvc exp run --queue -S conv_units=256
+```
+
+Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+
+```dvc
+$ dvc exp run --run-all --jobs 2
+TK
+```
+
+## Comparing experiments
+
+The pipeline is run several times with different parameters. To compare all of
+these experiments, we use `dvc exp show`. This command presents the parameters
+and metrics produced in experiments in a nicely formatted table.
+
+```dvc
+$ dvc exp show
+```
+
+TK
+
+By default it shows all the parameters and the metrics along with the timestamp.
+If you have large number of parameters, metrics or experiments, this may lead to
+a cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
+
+```dvc
+$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
+TK
+```
+
+## Persisting experiments
+
+After selecting a experiments from the table, you can commit the hyperparameters
+and other dependencies that produced this successful experiment to your Git
+history.
+
+`dvc exp apply` brings back all specific artifacts and parameters from the
+experiment to the <abbr>workspace</abbr>.
+
+```dvc
+$ dvc exp apply
+TK
+```
+
+We can see the changes in the repository and commit them to Git.
+
+```dvc
+$ git diff
+$ git add .
+$ git commit -m "Successful experiment"
+```
+
+### Preparing an experiments pipeline
+
+At the beginning of this document, we assumed that there is already a configured DVC project to simplify the introduction. DVC experiments are a feature added in DVC 2.0 and requires a DVC pipeline is defined in the project. In this section we'll show how to configure a project to run DVC experiments. You can get detailed information about these commands in other sections of DVC documentation.
+
+If DVC is not initialized before in the project, you can do so by:
+
+```dvc
+$ dvc init
+```
+
+DVC also requires commands to be run and their dependencies to be defined as stages. We use `dvc stage add` to add a stage and set its dependencies. 
+
+```dvc
+$ dvc stage add
+TK
+```
+
+Note that the parameters (added with `-p`) are in the default parameters file `params.yaml` and used in the code as normal, by reading the file. DVC only tracks the changes and updates them with `--set-param`. 
+
+
+## Go Further
+
+You can continue to experiment with
+[the project](https://github.com/iterative/get-started-experiments). Please see
+the `README.md` file of the project for these. Don't forget to
+[notify us](https://dvc.org/chat) if you happen to find good parameters.
+
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
+
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From 29c3ae04cc7774993f02a567a2d28a6c441643de Mon Sep 17 00:00:00 2001
From: "restyled-io[bot]" <32688539+restyled-io[bot]@users.noreply.github.com>
Date: Mon, 5 Jul 2021 22:45:06 +0300
Subject: [PATCH 05/89] Restyled by prettier (#2608)

Co-authored-by: Restyled.io <commits@restyled.io>
---
 .../start/experiments-trail/experiments-2.md   | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 93d9250740..d42b924c4a 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -45,7 +45,8 @@ $ python -m pip install -r requirements.txt
 
 The repository you cloned doesn't contain the dataset. In order to get
 `fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc pull` to update
-the missing data files. `dvc pull` is used in DVC repositories to update the missing data dependencies. 
+the missing data files. `dvc pull` is used in DVC repositories to update the
+missing data dependencies.
 
 ```dvc
 $ dvc pull
@@ -194,7 +195,12 @@ $ git commit -m "Successful experiment"
 
 ### Preparing an experiments pipeline
 
-At the beginning of this document, we assumed that there is already a configured DVC project to simplify the introduction. DVC experiments are a feature added in DVC 2.0 and requires a DVC pipeline is defined in the project. In this section we'll show how to configure a project to run DVC experiments. You can get detailed information about these commands in other sections of DVC documentation.
+At the beginning of this document, we assumed that there is already a configured
+DVC project to simplify the introduction. DVC experiments are a feature added in
+DVC 2.0 and requires a DVC pipeline is defined in the project. In this section
+we'll show how to configure a project to run DVC experiments. You can get
+detailed information about these commands in other sections of DVC
+documentation.
 
 If DVC is not initialized before in the project, you can do so by:
 
@@ -202,15 +208,17 @@ If DVC is not initialized before in the project, you can do so by:
 $ dvc init
 ```
 
-DVC also requires commands to be run and their dependencies to be defined as stages. We use `dvc stage add` to add a stage and set its dependencies. 
+DVC also requires commands to be run and their dependencies to be defined as
+stages. We use `dvc stage add` to add a stage and set its dependencies.
 
 ```dvc
 $ dvc stage add
 TK
 ```
 
-Note that the parameters (added with `-p`) are in the default parameters file `params.yaml` and used in the code as normal, by reading the file. DVC only tracks the changes and updates them with `--set-param`. 
-
+Note that the parameters (added with `-p`) are in the default parameters file
+`params.yaml` and used in the code as normal, by reading the file. DVC only
+tracks the changes and updates them with `--set-param`.
 
 ## Go Further
 

From e12f22205c4d9860210131275613db6652e8bfe8 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 00:13:27 +0300
Subject: [PATCH 06/89] Update version 1 by some command outputs

---
 .../start/experiments-trail/experiments-1.md  | 87 +++++++++++++------
 1 file changed, 62 insertions(+), 25 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 08f7a9e7fb..59da7fe053 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -68,6 +68,21 @@ We first initialize DVC inside the project to create an experiment.
 $ dvc init
 ```
 
+Now, we can add the dataset to the project:
+
+```dvc
+$ dvc add data/images
+```
+
+This creates a `data/images.dvc` file that contains all the relevant metadata of
+the directory. You can add and commit the corresponding `.dvc` file and changes
+in `.gitignore` that hides the `data/images/` directory from Git.
+
+```dvc
+$ git add data/.gitignore data/images.dvc
+$ git commit -m "Dataset added"
+```
+
 DVC experiments are run by specifying their commands, outputs, parameters and
 dependencies. We add an experiment command by `dvc stage add`.
 
@@ -92,22 +107,29 @@ $ git add dvc.yaml .gitignore
 $ git commit -m "added data and the experiment"
 ```
 
-</details>
+DVC is ready to run the experiments now!
 
-## Running experiments
+</details>
 
-### Running with default parameters
+## Running the experiment with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment is tracked by DVC and persisted on demand.
 
-Running the pipeline with default values requires only the command:
+Running the experiment with default hyperparameter values requires only the
+command:
 
 ```dvc
 $ dvc exp run
-TK
+...
+Reproduced experiment(s): exp-7683f
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
 ```
 
 It runs the pipeline starting from the basic dependencies and produces
@@ -135,7 +157,7 @@ features.
 
 </details>
 
-### Running by setting parameters
+## Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -144,22 +166,31 @@ the files manually. We use this feature to set the convolutional units in
 `train.py`.
 
 ```dvc
-$ dvc exp run --set-param conv_units=24
-TK
-```
+$ dvc exp run --set-param model.conv_units=24
+...
+Reproduced experiment(s): exp-6c06d
+Experiment results have been applied to your workspace.
 
-Note that the pipeline didn't run the earliest stage. Only the stages that
-depend on the updated parameter and subsequent stages are run.
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
+```
 
 When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
 can see the effect of it by looking at the diff.
 
 ```dvc
 $ git diff params.yaml
-TK
 ```
 
-### Run multiple experiments in parallel
+```git
+-model:
+-  conv_units: 16
++model:
++  conv_units: 24
+```
+
+## Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them first to run
 them in a batch. This is especially handy when you have long running
@@ -168,19 +199,22 @@ experiments.
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
 
-```dvc
-$ dvc exp run --queue -S conv_units=32
-$ dvc exp run --queue -S conv_units=64
-$ dvc exp run --queue -S conv_units=128
-$ dvc exp run --queue -S conv_units=256
-```
+````dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '30eb9b2' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment 'ac66940' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '8bb6049' for future execution.```
 
 Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
 TK
-```
+````
 
 ## Comparing experiments
 
@@ -227,12 +261,15 @@ $ git add .
 $ git commit -m "Successful experiment"
 ```
 
-## Go Further
+It may also be desirable to commit a particular experiment to a Git branch
+directly, without bringing to the workspace.
 
-You can continue to experiment with
-[the project](https://github.com/iterative/get-started-experiments). Please see
-the `README.md` file of the project for these. Don't forget to
-[notify us](https://dvc.org/chat) if you happen to find good parameters.
+```dvc
+$ dvc exp branch exp-
+TK
+```
+
+## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From 1a646bba12c1b11f0c0d50926a9811bd4d5e38a0 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 12:53:49 +0300
Subject: [PATCH 07/89] Added naming section and two screenshots to draft 1

---
 .../start/experiments-trail/experiments-1.md  |  78 +++++++++++++++---
 static/img/start-dvc-exp-show-210704.png      | Bin 0 -> 218492 bytes
 ...start-dvc-exp-show-no-timestamp-210704.png | Bin 0 -> 125016 bytes
 3 files changed, 67 insertions(+), 11 deletions(-)
 create mode 100644 static/img/start-dvc-exp-show-210704.png
 create mode 100644 static/img/start-dvc-exp-show-no-timestamp-210704.png

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 59da7fe053..b63f4f6de9 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -21,7 +21,8 @@ with `[get-started-experiments]` project.
 get-started-experiments: https://github.com/iterative/get-started-experiments
 
 <details>
-## Installing and Configuring the Project
+
+### Installing and Configuring the Project
 
 These commands are run in the `[get-started-experiments]` project. You can run
 the commands in this document after cloning the repository and installing the
@@ -116,7 +117,7 @@ DVC is ready to run the experiments now!
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment is tracked by DVC and persisted on demand.
+produced for each experiment are tracked by DVC and persisted on demand.
 
 Running the experiment with default hyperparameter values requires only the
 command:
@@ -207,15 +208,17 @@ Queued experiment '30eb9b2' for future execution.
 $ dvc exp run --queue -S model.conv_units=128
 Queued experiment 'ac66940' for future execution.
 $ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.```
+Queued experiment '8bb6049' for future execution.
+```
 
 Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
-TK
 ````
 
+It runs all the experiments with different processes.
+
 ## Comparing experiments
 
 The pipeline is run several times with different parameters. To compare all of
@@ -226,7 +229,7 @@ and metrics produced in experiments in a nicely formatted table.
 $ dvc exp show
 ```
 
-TK
+![](/img/start-dvc-exp-show-210704.png)
 
 By default it shows all the parameters and the metrics along with the timestamp.
 If you have large number of parameters, metrics or experiments, this may lead to
@@ -235,10 +238,11 @@ hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
 ```dvc
-$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
-TK
+$ dvc exp show --no-timestamp --include-params model.conv_units --include-metrics acc
 ```
 
+![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+
 ## Persisting experiments
 
 After selecting a experiments from the table, you can commit the hyperparameters
@@ -249,8 +253,8 @@ history.
 experiment to the <abbr>workspace</abbr>.
 
 ```dvc
-$ dvc exp apply
-TK
+$ dvc exp apply exp-cb13f
+Changes for experiment 'exp-cb13f' have been applied to your current workspace.
 ```
 
 We can see the changes in the repository and commit them to Git.
@@ -265,10 +269,62 @@ It may also be desirable to commit a particular experiment to a Git branch
 directly, without bringing to the workspace.
 
 ```dvc
-$ dvc exp branch exp-
-TK
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
+
+        git checkout cnn-256
 ```
 
+You can then checkout and continue from working this branch as usual.
+
+## A note on experiment names
+
+When you create an experiment, DVC generates a hash value from the contents of
+the experiment. This is shown when you use `--queue` option, e.g.,
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+```
+
+After _running_ the experiment, DVC uses another auto-generated name to refer to
+the experiment. Typically these start with `exp-` by default, and can be set via
+`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
+the name, you can see the hash value:
+
+```dvc
+$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
+Queued experiment '86bd8f9' for future execution.
+```
+
+In `dvc exp show` you can see both of these names:
+
+```dvc
+$ dvc exp show --no-pager --no-timestamp \
+      --include-metrics loss --include-params model.conv_units
+
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ Experiment              ┃ loss    ┃ model.conv_units ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.23534 │ 64               │
+│ 3973b6b                 │ -       │ 16               │
+│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
+│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
+│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
+│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
+│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
+│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
+│ └── *86bd8f9            │ -       │ 512              │
+└─────────────────────────┴─────────┴──────────────────┘
+```
+
+When an experiment is not run yet, only the former hash value is shown.
+
+You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
+running the experiment with the name starting with `exp-`, or the name you have
+supplied with `dvc exp run --name`.
+
 ## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
diff --git a/static/img/start-dvc-exp-show-210704.png b/static/img/start-dvc-exp-show-210704.png
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From 5c37246aee18d3d6ad06ba75e59f8227933d0d6a Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 13:20:26 +0300
Subject: [PATCH 08/89] adding separate section for experiment preparation in
 draft 2

---
 .../start/experiments-trail/experiments-2.md  | 53 +++++++++++++------
 1 file changed, 37 insertions(+), 16 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index d42b924c4a..2fdc1e50b0 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -58,22 +58,30 @@ Then we extract this file that contains labeled images.
 $ tar -xvzf data/images.tar.gz --directory data/
 ```
 
-</details>
+The repository already contains the necessary configuration to run the
+experiments. If you would like to learn how to configure a project to run DVC
+experiments, please refer to the last section.
 
-## Running experiments
+</details>
 
-### Running with default parameters
+## Running the experiments with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment is tracked by DVC and persisted on demand.
+produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the pipeline with default values requires only the command:
+Running the experiments with default values requires only the command:
 
 ```dvc
 $ dvc exp run
-TK
+...
+Reproduced experiment(s): exp-7683f
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
 ```
 
 It runs the pipeline starting from the basic dependencies and produces
@@ -101,7 +109,7 @@ features.
 
 </details>
 
-### Running by setting parameters
+## Running the experiments by setting parameters
 
 Now let's do some more experimentation.
 
@@ -111,18 +119,27 @@ the files manually. We use this feature to set the convolutional units in
 
 ```dvc
 $ dvc exp run --set-param conv_units=24
-TK
-```
+...
+Reproduced experiment(s): exp-6c06d
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
 
-Note that the pipeline didn't run the earliest stage. Only the stages that
-depend on the updated parameter and subsequent stages are run.
+        dvc exp branch <exp>
+```
 
 When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
 can see the effect of it by looking at the diff.
 
 ```dvc
 $ git diff params.yaml
-TK
+```
+
+```git
+-model:
+-  conv_units: 16
++model:
++  conv_units: 24
 ```
 
 ### Run multiple experiments in parallel
@@ -135,10 +152,14 @@ We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
 
 ```dvc
-$ dvc exp run --queue -S conv_units=32
-$ dvc exp run --queue -S conv_units=64
-$ dvc exp run --queue -S conv_units=128
-$ dvc exp run --queue -S conv_units=256
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '30eb9b2' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment 'ac66940' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '8bb6049' for future execution.
 ```
 
 Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):

From 5756cfc3b3a91091b652c32c2ad1064b368fa73d Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 18:37:43 +0300
Subject: [PATCH 09/89] fixed link to the project and added some explanations
 to installation

---
 .../start/experiments-trail/experiments-1.md  | 36 +++++++++----------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index b63f4f6de9..da96512b54 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -12,21 +12,19 @@ your repo doesn't become polluted with all of them. You can discard experiments
 once they're no longer needed.
 
 Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). Let's further
-increase the number of features in the `featurize` stage to see how it compares.
+[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
+will explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
-In this section, we will explore the basic features of DVC experiment management
-with `[get-started-experiments]` project.
-
-get-started-experiments: https://github.com/iterative/get-started-experiments
+[gse]: https://github.com/iterative/get-started-experiments
 
 <details>
 
 ### Installing and Configuring the Project
 
-These commands are run in the `[get-started-experiments]` project. You can run
-the commands in this document after cloning the repository and installing the
-requirements.
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
 
 ### Clone the project and create virtual environment
 
@@ -46,8 +44,8 @@ $ python -m pip install -r requirements.txt
 ### Get the data set
 
 The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to download
-the missing data files. `dvc get` is similar to `wget` but works with Git+DVC
+`fashion-mnist.tar.gz` from `dataset-registry`, we use `dvc get` to download the
+missing data files. `dvc get` is similar to `wget` but works with Git+DVC
 repositories to download binary files.
 
 ```dvc
@@ -61,7 +59,7 @@ Then we extract this file that contains labeled images.
 $ tar -xvzf data/images.tar.gz --directory data/
 ```
 
-### Specifying the experiment
+### Specify the experiment
 
 We first initialize DVC inside the project to create an experiment.
 
@@ -69,15 +67,15 @@ We first initialize DVC inside the project to create an experiment.
 $ dvc init
 ```
 
-Now, we can add the dataset to the project:
+Then we add the dataset to the project:
 
 ```dvc
 $ dvc add data/images
 ```
 
 This creates a `data/images.dvc` file that contains all the relevant metadata of
-the directory. You can add and commit the corresponding `.dvc` file and changes
-in `.gitignore` that hides the `data/images/` directory from Git.
+the directory. You can add and commit `data/images.dvc` file, and changes in
+`.gitignore` that hides the `data/images/` directory from Git.
 
 ```dvc
 $ git add data/.gitignore data/images.dvc
@@ -85,7 +83,7 @@ $ git commit -m "Dataset added"
 ```
 
 DVC experiments are run by specifying their commands, outputs, parameters and
-dependencies. We add an experiment command by `dvc stage add`.
+dependencies. We specify an experiment command by `dvc stage add`.
 
 ```dvc
 $ dvc stage add -n train \
@@ -97,8 +95,10 @@ $ dvc stage add -n train \
 ```
 
 The command tells DVC to create an experiment named `train`, with two parameters
-and a data dependency to `data/images`. The command produces `metrics.json` as a
-special type of output.
+and a dependency to `data/images`. The command produces `metrics.json` as a
+special type of output. Basically it tells DVC that for any change in
+`data/images/`, `model.conv_units` or `train.epochs`, we run an experiment using
+`src/train.py` that produces a new `metrics.json` file.
 
 DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
 artifacts.

From 1645b107d42a62b8d124c5838217b2603809583c Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 18:45:40 +0300
Subject: [PATCH 10/89] some minor edits in draft 1

---
 .../docs/start/experiments-trail/experiments-1.md  | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index da96512b54..41179baa9a 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -114,7 +114,7 @@ DVC is ready to run the experiments now!
 
 ## Running the experiment with default parameters
 
-The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
@@ -141,7 +141,7 @@ It runs the pipeline starting from the basic dependencies and produces
 ### If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may be used to `dvc repro`.
+have a DVC project, you may already be using `dvc repro`.
 
 In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
 pipeline.
@@ -149,12 +149,12 @@ pipeline.
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
 All the parameters and dependencies are retrieved from the current workspace. It
 doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit into Git, it's better to use
-`dvc exp run`. It allows to change the parameters quickly, can track the history
-of artifacts and has facilities to compare these experiments easily.
+number of experiments that you don't want to commit all to Git, it's better to
+use `dvc exp run`. It allows to change the parameters quickly, can track the
+history of artifacts and has facilities to compare these experiments easily.
 
-`dvc repro` is still available to run the pipeline that don't need these extra
-features.
+`dvc repro` is still available to run the pipeline when these extra features are
+not needed.
 
 </details>
 

From 0acdd1388a7d0f4c8463f03af0cafb07f5800725 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 19:19:11 +0300
Subject: [PATCH 11/89] minor edits in pipeline explanation

---
 .../start/experiments-trail/experiments-1.md  | 40 +++++++++----------
 1 file changed, 19 insertions(+), 21 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 41179baa9a..c0d2dde4dd 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -94,11 +94,9 @@ $ dvc stage add -n train \
                 python3 src/train.py
 ```
 
-The command tells DVC to create an experiment named `train`, with two parameters
-and a dependency to `data/images`. The command produces `metrics.json` as a
-special type of output. Basically it tells DVC that for any change in
-`data/images/`, `model.conv_units` or `train.epochs`, we run an experiment using
-`src/train.py` that produces a new `metrics.json` file.
+The command tells DVC to create an experiment named `train`, and that for any
+change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
+experiment using `src/train.py` that produces a new `metrics.json` file.
 
 DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
 artifacts.
@@ -193,14 +191,13 @@ $ git diff params.yaml
 
 ## Run multiple experiments in parallel
 
-Instead of running the experiments one-by-one, we can define them first to run
-them in a batch. This is especially handy when you have long running
-experiments.
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
 
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
 
-````dvc
+```dvc
 $ dvc exp run --queue -S model.conv_units=32
 Queued experiment '6518f17' for future execution.
 $ dvc exp run --queue -S model.conv_units=64
@@ -215,15 +212,15 @@ Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
-````
+```
 
-It runs all the experiments with different processes.
+It runs all the experiments, with the specified number of processes in parallel.
 
 ## Comparing experiments
 
-The pipeline is run several times with different parameters. To compare all of
-these experiments, we use `dvc exp show`. This command presents the parameters
-and metrics produced in experiments in a nicely formatted table.
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
 
 ```dvc
 $ dvc exp show
@@ -231,14 +228,15 @@ $ dvc exp show
 
 ![](/img/start-dvc-exp-show-210704.png)
 
-By default it shows all the parameters and the metrics along with the timestamp.
-If you have large number of parameters, metrics or experiments, this may lead to
-a cluttered view. You can limit the table to specific metrics, or parameters, or
+By default it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
 ```dvc
-$ dvc exp show --no-timestamp --include-params model.conv_units --include-metrics acc
+$ dvc exp show --no-timestamp \
+  --include-params model.conv_units --include-metrics acc
 ```
 
 ![](/img/start-dvc-exp-show-no-timestamp-210704.png)
@@ -278,7 +276,7 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## A note on experiment names
+## Note on experiment names
 
 When you create an experiment, DVC generates a hash value from the contents of
 the experiment. This is shown when you use `--queue` option, e.g.,
@@ -289,9 +287,9 @@ Queued experiment '6518f17' for future execution.
 ```
 
 After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-` by default, and can be set via
+the experiment. Typically these start with `exp-`, and can be set via
 `--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value:
+the name, you can see the hash value as _queued experiment_:
 
 ```dvc
 $ dvc exp run --queue --name cnn-512 -S model.conv_units=512

From 0f43b57b7af8d0c9795e3f7f9dd70babfcf63129 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 19:19:33 +0300
Subject: [PATCH 12/89] carried over changes in draft-1 and updated the install
 instructions

---
 .../start/experiments-trail/experiments-2.md  | 171 ++++++++++++------
 1 file changed, 119 insertions(+), 52 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 2fdc1e50b0..5a6c0dd5fc 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -12,19 +12,19 @@ your repo doesn't become polluted with all of them. You can discard experiments
 once they're no longer needed.
 
 Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). Let's further
-increase the number of features in the `featurize` stage to see how it compares.
+[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
+will explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
-In this section, we will explore the basic features of DVC experiment management
-with `[get-started-experiments]` project.
+[gse]: https://github.com/iterative/get-started-experiments
 
-get-started-experiments: https://github.com/iterative/get-started-experiments
+<details>
 
-## Installing and Configuring the Project
+## Installing the Project
 
-These commands are run in the `[get-started-experiments]` project. You can run
-the commands in this document after cloning the repository and installing the
-requirements.
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
 
 ### Clone the project and create virtual environment
 
@@ -43,10 +43,9 @@ $ python -m pip install -r requirements.txt
 
 ### Get the data set
 
-The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc pull` to update
-the missing data files. `dvc pull` is used in DVC repositories to update the
-missing data dependencies.
+The repository we cloned doesn't contain the dataset. In order to get the
+dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
+in DVC repositories to update the missing data dependencies.
 
 ```dvc
 $ dvc pull
@@ -64,14 +63,15 @@ experiments, please refer to the last section.
 
 </details>
 
-## Running the experiments with default parameters
+## Running the experiment with default parameters
 
-The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the experiments with default values requires only the command:
+Running the experiment with default hyperparameter values requires only the
+command:
 
 ```dvc
 $ dvc exp run
@@ -92,7 +92,7 @@ It runs the pipeline starting from the basic dependencies and produces
 ### If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may be used to `dvc repro`.
+have a DVC project, you may already be using `dvc repro`.
 
 In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
 pipeline.
@@ -100,16 +100,16 @@ pipeline.
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
 All the parameters and dependencies are retrieved from the current workspace. It
 doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit into Git, it's better to use
-`dvc exp run`. It allows to change the parameters quickly, can track the history
-of artifacts and has facilities to compare these experiments easily.
+number of experiments that you don't want to commit all to Git, it's better to
+use `dvc exp run`. It allows to change the parameters quickly, can track the
+history of artifacts and has facilities to compare these experiments easily.
 
-`dvc repro` is still available to run the pipeline that don't need these extra
-features.
+`dvc repro` is still available to run the pipeline when these extra features are
+not needed.
 
 </details>
 
-## Running the experiments by setting parameters
+## Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -118,7 +118,7 @@ the files manually. We use this feature to set the convolutional units in
 `train.py`.
 
 ```dvc
-$ dvc exp run --set-param conv_units=24
+$ dvc exp run --set-param model.conv_units=24
 ...
 Reproduced experiment(s): exp-6c06d
 Experiment results have been applied to your workspace.
@@ -142,11 +142,10 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
-### Run multiple experiments in parallel
+## Run multiple experiments in parallel
 
-Instead of running the experiments one-by-one, we can define them first to run
-them in a batch. This is especially handy when you have long running
-experiments.
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
 
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
@@ -166,32 +165,35 @@ Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
-TK
 ```
 
+It runs all the experiments, with the specified number of processes in parallel.
+
 ## Comparing experiments
 
-The pipeline is run several times with different parameters. To compare all of
-these experiments, we use `dvc exp show`. This command presents the parameters
-and metrics produced in experiments in a nicely formatted table.
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
 
 ```dvc
 $ dvc exp show
 ```
 
-TK
+![](/img/start-dvc-exp-show-210704.png)
 
-By default it shows all the parameters and the metrics along with the timestamp.
-If you have large number of parameters, metrics or experiments, this may lead to
-a cluttered view. You can limit the table to specific metrics, or parameters, or
+By default it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
 ```dvc
-$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
-TK
+$ dvc exp show --no-timestamp \
+  --include-params model.conv_units --include-metrics acc
 ```
 
+![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+
 ## Persisting experiments
 
 After selecting a experiments from the table, you can commit the hyperparameters
@@ -202,8 +204,8 @@ history.
 experiment to the <abbr>workspace</abbr>.
 
 ```dvc
-$ dvc exp apply
-TK
+$ dvc exp apply exp-cb13f
+Changes for experiment 'exp-cb13f' have been applied to your current workspace.
 ```
 
 We can see the changes in the repository and commit them to Git.
@@ -214,14 +216,74 @@ $ git add .
 $ git commit -m "Successful experiment"
 ```
 
-### Preparing an experiments pipeline
+It may also be desirable to commit a particular experiment to a Git branch
+directly, without bringing to the workspace.
+
+```dvc
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
+
+        git checkout cnn-256
+```
+
+You can then checkout and continue from working this branch as usual.
+
+## Note on experiment names
+
+When you create an experiment, DVC generates a hash value from the contents of
+the experiment. This is shown when you use `--queue` option, e.g.,
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+```
+
+After _running_ the experiment, DVC uses another auto-generated name to refer to
+the experiment. Typically these start with `exp-`, and can be set via
+`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
+the name, you can see the hash value as _queued experiment_:
+
+```dvc
+$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
+Queued experiment '86bd8f9' for future execution.
+```
+
+In `dvc exp show` you can see both of these names:
+
+```dvc
+$ dvc exp show --no-pager --no-timestamp \
+      --include-metrics loss --include-params model.conv_units
+
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ Experiment              ┃ loss    ┃ model.conv_units ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.23534 │ 64               │
+│ 3973b6b                 │ -       │ 16               │
+│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
+│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
+│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
+│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
+│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
+│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
+│ └── *86bd8f9            │ -       │ 512              │
+└─────────────────────────┴─────────┴──────────────────┘
+```
+
+When an experiment is not run yet, only the former hash value is shown.
+
+You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
+running the experiment with the name starting with `exp-`, or the name you have
+supplied with `dvc exp run --name`.
+
+## Preparing a project for DVC experiments
 
 At the beginning of this document, we assumed that there is already a configured
 DVC project to simplify the introduction. DVC experiments are a feature added in
-DVC 2.0 and requires a DVC pipeline is defined in the project. In this section
-we'll show how to configure a project to run DVC experiments. You can get
-detailed information about these commands in other sections of DVC
-documentation.
+DVC 2.0 and requires a DVC pipeline defined in the project. In this section
+we'll show how to configure a project to run DVC experiments.
+
+Please refer to [install](/doc/install) if DVC is not installed in your system.
 
 If DVC is not initialized before in the project, you can do so by:
 
@@ -233,20 +295,25 @@ DVC also requires commands to be run and their dependencies to be defined as
 stages. We use `dvc stage add` to add a stage and set its dependencies.
 
 ```dvc
-$ dvc stage add
-TK
+$ dvc stage add -n train \
+                -p model.conv_units \
+                -p train.epochs \
+                -d data/images \
+                -m metrics.json \
+                python3 src/train.py
 ```
 
+The command tells DVC to create an experiment named `train`, and that for any
+change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
+experiment using `src/train.py` that produces a new `metrics.json` file.
+
 Note that the parameters (added with `-p`) are in the default parameters file
 `params.yaml` and used in the code as normal, by reading the file. DVC only
 tracks the changes and updates them with `--set-param`.
 
-## Go Further
+DVC is ready to run the experiments now!
 
-You can continue to experiment with
-[the project](https://github.com/iterative/get-started-experiments). Please see
-the `README.md` file of the project for these. Don't forget to
-[notify us](https://dvc.org/chat) if you happen to find good parameters.
+## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From 2f1cd50972705f9e98ff102f46c71524beccabd2 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 8 Jul 2021 12:50:19 +0300
Subject: [PATCH 13/89] merged and simplified the first paragraph and added
 emojis

---
 .../start/experiments-trail/experiments-1.md  | 38 ++++++++-----------
 1 file changed, 16 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index c0d2dde4dd..34c12c77bf 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -4,29 +4,23 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
-will explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
+<abbr>Experiments</abbr> grow in numbers where there are many parameters to
+tune. We can organize such experiments and keep only what we ultimately need
+with `dvc experiments`. DVC can track experiments for you so there's no need to
+commit each one to Git. We explore the basic features of DVC experiment
+management with [`get-started-experiments`][gse] project in this section.
 
 [gse]: https://github.com/iterative/get-started-experiments
 
 <details>
 
-### Installing and Configuring the Project
+### ⚙️ Installing and Configuring the Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### Clone the project and create virtual environment
+### 👥 Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -41,7 +35,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### Get the data set
+### 📀 Get the data set
 
 The repository you cloned doesn't contain the dataset. In order to get
 `fashion-mnist.tar.gz` from `dataset-registry`, we use `dvc get` to download the
@@ -59,7 +53,7 @@ Then we extract this file that contains labeled images.
 $ tar -xvzf data/images.tar.gz --directory data/
 ```
 
-### Specify the experiment
+### 🏹 Specify the experiment
 
 We first initialize DVC inside the project to create an experiment.
 
@@ -110,7 +104,7 @@ DVC is ready to run the experiments now!
 
 </details>
 
-## Running the experiment with default parameters
+## 👟 Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
@@ -136,7 +130,7 @@ It runs the pipeline starting from the basic dependencies and produces
 
 <details>
 
-### If you used `dvc repro` before
+### 📜 If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -156,7 +150,7 @@ not needed.
 
 </details>
 
-## Running the experiment by setting parameters
+## 🧥 Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -189,7 +183,7 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
-## Run multiple experiments in parallel
+## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -241,7 +235,7 @@ $ dvc exp show --no-timestamp \
 
 ![](/img/start-dvc-exp-show-no-timestamp-210704.png)
 
-## Persisting experiments
+## 🔏 Persisting experiments
 
 After selecting a experiments from the table, you can commit the hyperparameters
 and other dependencies that produced this successful experiment to your Git
@@ -276,7 +270,7 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## Note on experiment names
+## 📛 Note on experiment names
 
 When you create an experiment, DVC generates a hash value from the contents of
 the experiment. This is shown when you use `--queue` option, e.g.,
@@ -323,7 +317,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## Go Further
+## 🪐 Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From 51aa9da885e6d9cab590e303383decb8d57d51c7 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 8 Jul 2021 12:53:55 +0300
Subject: [PATCH 14/89] added links to the sidebar (tentative)

---
 content/docs/sidebar.json | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index 1a79209f4f..43e85fbe58 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -34,6 +34,14 @@
       "katacoda": "https://katacoda.com/dvc/courses/get-started"
     },
     "children": [
+      {
+        "slug": "experiments-trail/experiments-1",
+        "label": "Experiments Trail (Alternative 1)"
+      },
+      {
+        "slug": "experiments-trail/experiments-2",
+        "label": "Experiments Trail (Alternative 2)"
+      },
       {
         "slug": "data-and-model-versioning",
         "tutorials": {

From 9f251433e01b716caf35ae5c96cda835ee68c633 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 9 Jul 2021 13:15:15 +0300
Subject: [PATCH 15/89] changes after jorge's review

---
 .../start/experiments-trail/experiments-1.md   | 18 ++++++------------
 1 file changed, 6 insertions(+), 12 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 34c12c77bf..12cd0b6589 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -111,22 +111,17 @@ experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the experiment with default hyperparameter values requires only the
-command:
+Running the experiment with default project settings requires only the command:
 
 ```dvc
 $ dvc exp run
 ...
 Reproduced experiment(s): exp-7683f
 Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
+...
 ```
 
-It runs the pipeline starting from the basic dependencies and produces
-`metrics.json` file for the default state.
+It runs the specified command that writes the metrics values to `metrics.json`.
 
 <details>
 
@@ -202,14 +197,13 @@ $ dvc exp run --queue -S model.conv_units=256
 Queued experiment '8bb6049' for future execution.
 ```
 
-Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
 ```
 
-It runs all the experiments, with the specified number of processes in parallel.
-
 ## Comparing experiments
 
 The experiments are run several times with different parameters. We use
@@ -237,7 +231,7 @@ $ dvc exp show --no-timestamp \
 
 ## 🔏 Persisting experiments
 
-After selecting a experiments from the table, you can commit the hyperparameters
+After selecting an experiment from the table, you can commit the hyperparameters
 and other dependencies that produced this successful experiment to your Git
 history.
 

From e24d16392de801b7a5619f54c3cb57ebed7874dc Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Mon, 12 Jul 2021 13:09:06 +0300
Subject: [PATCH 16/89] carried over changes in alt-1 to alt-2

---
 .../start/experiments-trail/experiments-2.md  | 38 ++++++++-----------
 1 file changed, 16 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 5a6c0dd5fc..43bd2af1cc 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -20,13 +20,13 @@ will explore the basic features of DVC experiment management with
 
 <details>
 
-## Installing the Project
+## ⚙️ Installing the Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### Clone the project and create virtual environment
+### 👥 Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -41,7 +41,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### Get the data set
+### 📀 Get the data set
 
 The repository we cloned doesn't contain the dataset. In order to get the
 dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
@@ -63,33 +63,28 @@ experiments, please refer to the last section.
 
 </details>
 
-## Running the experiment with default parameters
+## 👟 Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the experiment with default hyperparameter values requires only the
-command:
+Running the experiment with default project settings requires only the command:
 
 ```dvc
 $ dvc exp run
 ...
 Reproduced experiment(s): exp-7683f
 Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
+...
 ```
 
-It runs the pipeline starting from the basic dependencies and produces
-`metrics.json` file for the default state.
+It runs the specified command that writes the metrics values to `metrics.json`.
 
 <details>
 
-### If you used `dvc repro` before
+### 📜 If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -109,7 +104,7 @@ not needed.
 
 </details>
 
-## Running the experiment by setting parameters
+## 🧥 Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -142,7 +137,7 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
-## Run multiple experiments in parallel
+## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -161,14 +156,13 @@ $ dvc exp run --queue -S model.conv_units=256
 Queued experiment '8bb6049' for future execution.
 ```
 
-Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
 ```
 
-It runs all the experiments, with the specified number of processes in parallel.
-
 ## Comparing experiments
 
 The experiments are run several times with different parameters. We use
@@ -194,9 +188,9 @@ $ dvc exp show --no-timestamp \
 
 ![](/img/start-dvc-exp-show-no-timestamp-210704.png)
 
-## Persisting experiments
+## 🔏 Persisting experiments
 
-After selecting a experiments from the table, you can commit the hyperparameters
+After selecting an experiment from the table, you can commit the hyperparameters
 and other dependencies that produced this successful experiment to your Git
 history.
 
@@ -229,7 +223,7 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## Note on experiment names
+## 📛 Note on experiment names
 
 When you create an experiment, DVC generates a hash value from the contents of
 the experiment. This is shown when you use `--queue` option, e.g.,
@@ -276,7 +270,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## Preparing a project for DVC experiments
+## ⏲ Preparing a project for DVC experiments
 
 At the beginning of this document, we assumed that there is already a configured
 DVC project to simplify the introduction. DVC experiments are a feature added in

From da4d6175eddace91171245eee239f51b0cfca5a2 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Mon, 12 Jul 2021 13:18:26 +0300
Subject: [PATCH 17/89] added 3rd alternative to experiments trail

---
 content/docs/sidebar.json                     |   4 +
 .../start/experiments-trail/experiments-3.md  | 319 ++++++++++++++++++
 2 files changed, 323 insertions(+)
 create mode 100644 content/docs/start/experiments-trail/experiments-3.md

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index 43e85fbe58..b3db277a97 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -42,6 +42,10 @@
         "slug": "experiments-trail/experiments-2",
         "label": "Experiments Trail (Alternative 2)"
       },
+      {
+        "slug": "experiments-trail/experiments-3",
+        "label": "Experiments Trail (Alternative 3)"
+      },
       {
         "slug": "data-and-model-versioning",
         "tutorials": {
diff --git a/content/docs/start/experiments-trail/experiments-3.md b/content/docs/start/experiments-trail/experiments-3.md
new file mode 100644
index 0000000000..b86b7db544
--- /dev/null
+++ b/content/docs/start/experiments-trail/experiments-3.md
@@ -0,0 +1,319 @@
+---
+title: 'Get Started: Experiments'
+---
+
+# Get Started with Experiments
+
+<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
+parameters to tune or other permutations of the code. We can organize such
+projects and keep only what we ultimately need with `dvc experiments`. DVC can
+track experiments for you so there's no need to commit each one to Git. This way
+your repo doesn't become polluted with all of them. You can discard experiments
+once they're no longer needed.
+
+Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
+[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
+will explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
+
+[gse]: https://github.com/iterative/get-started-experiments
+
+## ⚙️ Installing the Example Project
+
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
+
+### 👥 Clone the project and create virtual environment
+
+Please clone the project and create a virtual environment.
+
+> We create a virtual environment to keep the libraries we use isolated from the
+> rest of your system. This prevents version conflicts.
+
+```dvc
+$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
+```
+
+### 📀 Get the data set
+
+The repository we cloned doesn't contain the dataset. In order to get the
+dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
+in DVC repositories to update the missing data dependencies.
+
+```dvc
+$ dvc pull
+```
+
+Then we extract this file that contains labeled images.
+
+```dvc
+$ tar -xvzf data/images.tar.gz --directory data/
+```
+
+The repository already contains the necessary configuration to run the
+experiments. If you would like to learn how to configure a project to run DVC
+experiments, please refer to the last section.
+
+<details>
+
+## ⏲ Preparing a project for DVC experiments
+
+In this document we assume that there is already a configured DVC project to
+simplify the introduction. DVC experiments are a feature added in DVC 2.0 and
+requires a DVC pipeline defined in the project.
+
+Please refer to [install](/doc/install) if DVC is not installed in your system.
+
+If DVC is not initialized before in the project, you can do so by:
+
+```dvc
+$ dvc init
+```
+
+DVC also requires commands to be run and their dependencies to be defined as
+stages. We use `dvc stage add` to add a stage and set its dependencies.
+
+```dvc
+$ dvc stage add -n train \
+                -p model.conv_units \
+                -p train.epochs \
+                -d data/images \
+                -m metrics.json \
+                python3 src/train.py
+```
+
+The command tells DVC to create an experiment named `train`, and that for any
+change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
+experiment using `src/train.py` that produces a new `metrics.json` file.
+
+Note that the parameters (added with `-p`) are in the default parameters file
+`params.yaml` and used in the code as normal, by reading the file. DVC only
+tracks the changes and updates them with `--set-param`. For other files that
+contain the parameters, DVC expects the filename to be provided similar to
+`-p myparams.yaml:epochs`.
+
+DVC is ready to run the experiments now!
+
+</details>
+
+## 👟 Running the experiment with default parameters
+
+The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
+experiments. By _ephemeral_ we mean the experiments can be run without
+committing parameter and dependency changes to Git. Instead the artifacts
+produced for each experiment are tracked by DVC and persisted on demand.
+
+Running the experiment with default project settings requires only the command:
+
+```dvc
+$ dvc exp run
+...
+Reproduced experiment(s): exp-7683f
+Experiment results have been applied to your workspace.
+...
+```
+
+It runs the specified command that writes the metrics values to `metrics.json`.
+
+<details>
+
+### 📜 If you used `dvc repro` before
+
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may already be using `dvc repro`.
+
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
+pipeline.
+
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments. When you have large
+number of experiments that you don't want to commit all to Git, it's better to
+use `dvc exp run`. It allows to change the parameters quickly, can track the
+history of artifacts and has facilities to compare these experiments easily.
+
+`dvc repro` is still available to run the pipeline when these extra features are
+not needed.
+
+</details>
+
+## 🧥 Running the experiment by setting parameters
+
+Now let's do some more experimentation.
+
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
+
+```dvc
+$ dvc exp run --set-param model.conv_units=24
+...
+Reproduced experiment(s): exp-6c06d
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
+```
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
+can see the effect of it by looking at the diff.
+
+```dvc
+$ git diff params.yaml
+```
+
+```git
+-model:
+-  conv_units: 16
++model:
++  conv_units: 24
+```
+
+## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
+
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
+
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter.
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '30eb9b2' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment 'ac66940' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '8bb6049' for future execution.
+```
+
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
+
+```dvc
+$ dvc exp run --run-all --jobs 2
+```
+
+## Comparing experiments
+
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
+
+```dvc
+$ dvc exp show
+```
+
+![](/img/start-dvc-exp-show-210704.png)
+
+By default it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
+
+```dvc
+$ dvc exp show --no-timestamp \
+  --include-params model.conv_units --include-metrics acc
+```
+
+![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+
+## 🔏 Persisting experiments
+
+After selecting an experiment from the table, you can commit the hyperparameters
+and other dependencies that produced this successful experiment to your Git
+history.
+
+`dvc exp apply` brings back all specific artifacts and parameters from the
+experiment to the <abbr>workspace</abbr>.
+
+```dvc
+$ dvc exp apply exp-cb13f
+Changes for experiment 'exp-cb13f' have been applied to your current workspace.
+```
+
+We can see the changes in the repository and commit them to Git.
+
+```dvc
+$ git diff
+$ git add .
+$ git commit -m "Successful experiment"
+```
+
+It may also be desirable to commit a particular experiment to a Git branch
+directly, without bringing to the workspace.
+
+```dvc
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
+
+        git checkout cnn-256
+```
+
+You can then checkout and continue from working this branch as usual.
+
+## 📛 Note on experiment names
+
+When you create an experiment, DVC generates a hash value from the contents of
+the experiment. This is shown when you use `--queue` option, e.g.,
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+```
+
+After _running_ the experiment, DVC uses another auto-generated name to refer to
+the experiment. Typically these start with `exp-`, and can be set via
+`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
+the name, you can see the hash value as _queued experiment_:
+
+```dvc
+$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
+Queued experiment '86bd8f9' for future execution.
+```
+
+In `dvc exp show` you can see both of these names:
+
+```dvc
+$ dvc exp show --no-pager --no-timestamp \
+      --include-metrics loss --include-params model.conv_units
+
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ Experiment              ┃ loss    ┃ model.conv_units ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.23534 │ 64               │
+│ 3973b6b                 │ -       │ 16               │
+│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
+│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
+│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
+│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
+│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
+│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
+│ └── *86bd8f9            │ -       │ 512              │
+└─────────────────────────┴─────────┴──────────────────┘
+```
+
+When an experiment is not run yet, only the former hash value is shown.
+
+You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
+running the experiment with the name starting with `exp-`, or the name you have
+supplied with `dvc exp run --name`.
+
+## Go Further
+
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
+
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From 77c36c2af4f5ad83b6c445d42e7f271567a7fd5d Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Mon, 12 Jul 2021 13:47:12 +0300
Subject: [PATCH 18/89] minor changes

---
 content/docs/start/experiments-trail/experiments-1.md | 2 +-
 content/docs/start/experiments-trail/experiments-2.md | 4 ++--
 content/docs/start/experiments-trail/experiments-3.md | 4 ++--
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 12cd0b6589..44a334a33d 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -204,7 +204,7 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
-## Comparing experiments
+## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 43bd2af1cc..fb63cdb049 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -163,7 +163,7 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
-## Comparing experiments
+## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -307,7 +307,7 @@ tracks the changes and updates them with `--set-param`.
 
 DVC is ready to run the experiments now!
 
-## Go Further
+## 🪐 Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences
diff --git a/content/docs/start/experiments-trail/experiments-3.md b/content/docs/start/experiments-trail/experiments-3.md
index b86b7db544..46bbfcf116 100644
--- a/content/docs/start/experiments-trail/experiments-3.md
+++ b/content/docs/start/experiments-trail/experiments-3.md
@@ -201,7 +201,7 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
-## Comparing experiments
+## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -308,7 +308,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## Go Further
+## 🪐 Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From e76ff2b2d6a0e8f7b215521634dd840a5942eec4 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 16 Jul 2021 19:53:13 +0300
Subject: [PATCH 19/89] removed alt-1 and alt-2

---
 .../start/experiments-trail/experiments-1.md  | 322 ------------------
 .../start/experiments-trail/experiments-2.md  | 318 -----------------
 2 files changed, 640 deletions(-)
 delete mode 100644 content/docs/start/experiments-trail/experiments-1.md
 delete mode 100644 content/docs/start/experiments-trail/experiments-2.md

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
deleted file mode 100644
index 44a334a33d..0000000000
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ /dev/null
@@ -1,322 +0,0 @@
----
-title: 'Get Started: Experiments'
----
-
-# Get Started with Experiments
-
-<abbr>Experiments</abbr> grow in numbers where there are many parameters to
-tune. We can organize such experiments and keep only what we ultimately need
-with `dvc experiments`. DVC can track experiments for you so there's no need to
-commit each one to Git. We explore the basic features of DVC experiment
-management with [`get-started-experiments`][gse] project in this section.
-
-[gse]: https://github.com/iterative/get-started-experiments
-
-<details>
-
-### ⚙️ Installing and Configuring the Project
-
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
-
-### 👥 Clone the project and create virtual environment
-
-Please clone the project and create a virtual environment.
-
-> We create a virtual environment to keep the libraries we use isolated from the
-> rest of your system. This prevents version conflicts.
-
-```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b source-code
-$ cd get-started-experiments
-$ virtualenv .venv
-$ . .venv/bin/activate
-$ python -m pip install -r requirements.txt
-```
-
-### 📀 Get the data set
-
-The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from `dataset-registry`, we use `dvc get` to download the
-missing data files. `dvc get` is similar to `wget` but works with Git+DVC
-repositories to download binary files.
-
-```dvc
-$ dvc get https://github.com/iterative/dataset-registry \
-          fashion-mnist/images.tar.gz -o data/images.tar.gz
-```
-
-Then we extract this file that contains labeled images.
-
-```dvc
-$ tar -xvzf data/images.tar.gz --directory data/
-```
-
-### 🏹 Specify the experiment
-
-We first initialize DVC inside the project to create an experiment.
-
-```dvc
-$ dvc init
-```
-
-Then we add the dataset to the project:
-
-```dvc
-$ dvc add data/images
-```
-
-This creates a `data/images.dvc` file that contains all the relevant metadata of
-the directory. You can add and commit `data/images.dvc` file, and changes in
-`.gitignore` that hides the `data/images/` directory from Git.
-
-```dvc
-$ git add data/.gitignore data/images.dvc
-$ git commit -m "Dataset added"
-```
-
-DVC experiments are run by specifying their commands, outputs, parameters and
-dependencies. We specify an experiment command by `dvc stage add`.
-
-```dvc
-$ dvc stage add -n train \
-                -p model.conv_units \
-                -p train.epochs \
-                -d data/images \
-                -m metrics.json \
-                python3 src/train.py
-```
-
-The command tells DVC to create an experiment named `train`, and that for any
-change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
-experiment using `src/train.py` that produces a new `metrics.json` file.
-
-DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
-artifacts.
-
-```dvc
-$ git add dvc.yaml .gitignore
-$ git commit -m "added data and the experiment"
-```
-
-DVC is ready to run the experiments now!
-
-</details>
-
-## 👟 Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
-experiments. By _ephemeral_ we mean the experiments can be run without
-committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment are tracked by DVC and persisted on demand.
-
-Running the experiment with default project settings requires only the command:
-
-```dvc
-$ dvc exp run
-...
-Reproduced experiment(s): exp-7683f
-Experiment results have been applied to your workspace.
-...
-```
-
-It runs the specified command that writes the metrics values to `metrics.json`.
-
-<details>
-
-### 📜 If you used `dvc repro` before
-
-Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may already be using `dvc repro`.
-
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
-pipeline.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit all to Git, it's better to
-use `dvc exp run`. It allows to change the parameters quickly, can track the
-history of artifacts and has facilities to compare these experiments easily.
-
-`dvc repro` is still available to run the pipeline when these extra features are
-not needed.
-
-</details>
-
-## 🧥 Running the experiment by setting parameters
-
-Now let's do some more experimentation.
-
-DVC allows to update the parameters defined in the pipeline without modifying
-the files manually. We use this feature to set the convolutional units in
-`train.py`.
-
-```dvc
-$ dvc exp run --set-param model.conv_units=24
-...
-Reproduced experiment(s): exp-6c06d
-Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
-```
-
-When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
-can see the effect of it by looking at the diff.
-
-```dvc
-$ git diff params.yaml
-```
-
-```git
--model:
--  conv_units: 16
-+model:
-+  conv_units: 24
-```
-
-## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
-
-Instead of running the experiments one-by-one, we can define them to run in a
-batch. This is especially handy when you have long running experiments.
-
-We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter.
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-$ dvc exp run --queue -S model.conv_units=64
-Queued experiment '30eb9b2' for future execution.
-$ dvc exp run --queue -S model.conv_units=128
-Queued experiment 'ac66940' for future execution.
-$ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.
-```
-
-Next, run all (`--run-all`) queued experiments in parallel. You can specify the
-number of parallel processes using `--jobs`:
-
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
-
-## ↔️ Comparing experiments
-
-The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
-
-```dvc
-$ dvc exp show
-```
-
-![](/img/start-dvc-exp-show-210704.png)
-
-By default it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
-hide the timestamp column with `--include-metrics`, `--include-params`, or
-`--no-timestamp` options of the command, respectively.
-
-```dvc
-$ dvc exp show --no-timestamp \
-  --include-params model.conv_units --include-metrics acc
-```
-
-![](/img/start-dvc-exp-show-no-timestamp-210704.png)
-
-## 🔏 Persisting experiments
-
-After selecting an experiment from the table, you can commit the hyperparameters
-and other dependencies that produced this successful experiment to your Git
-history.
-
-`dvc exp apply` brings back all specific artifacts and parameters from the
-experiment to the <abbr>workspace</abbr>.
-
-```dvc
-$ dvc exp apply exp-cb13f
-Changes for experiment 'exp-cb13f' have been applied to your current workspace.
-```
-
-We can see the changes in the repository and commit them to Git.
-
-```dvc
-$ git diff
-$ git add .
-$ git commit -m "Successful experiment"
-```
-
-It may also be desirable to commit a particular experiment to a Git branch
-directly, without bringing to the workspace.
-
-```dvc
-$ dvc exp branch exp-05e87 "cnn-256"
-Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
-To switch to the new branch run:
-
-        git checkout cnn-256
-```
-
-You can then checkout and continue from working this branch as usual.
-
-## 📛 Note on experiment names
-
-When you create an experiment, DVC generates a hash value from the contents of
-the experiment. This is shown when you use `--queue` option, e.g.,
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-```
-
-After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-`, and can be set via
-`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value as _queued experiment_:
-
-```dvc
-$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
-Queued experiment '86bd8f9' for future execution.
-```
-
-In `dvc exp show` you can see both of these names:
-
-```dvc
-$ dvc exp show --no-pager --no-timestamp \
-      --include-metrics loss --include-params model.conv_units
-
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ Experiment              ┃ loss    ┃ model.conv_units ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.23534 │ 64               │
-│ 3973b6b                 │ -       │ 16               │
-│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
-│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
-│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
-│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
-│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
-│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
-│ └── *86bd8f9            │ -       │ 512              │
-└─────────────────────────┴─────────┴──────────────────┘
-```
-
-When an experiment is not run yet, only the former hash value is shown.
-
-You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
-running the experiment with the name starting with `exp-`, or the name you have
-supplied with `dvc exp run --name`.
-
-## 🪐 Go Further
-
-There are many other features of `dvc exp`, like cleaning up the unused
-experiments, sharing them without committing into Git or getting differences
-between two experiments.
-
-Please see the section on
-[Experiment Management](/doc/user-guide/experiment-management) in the User's
-Guide or `dvc exp` and subcommands in the Command Reference.
diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
deleted file mode 100644
index fb63cdb049..0000000000
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ /dev/null
@@ -1,318 +0,0 @@
----
-title: 'Get Started: Experiments'
----
-
-# Get Started with Experiments
-
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
-will explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
-
-[gse]: https://github.com/iterative/get-started-experiments
-
-<details>
-
-## ⚙️ Installing the Project
-
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
-
-### 👥 Clone the project and create virtual environment
-
-Please clone the project and create a virtual environment.
-
-> We create a virtual environment to keep the libraries we use isolated from the
-> rest of your system. This prevents version conflicts.
-
-```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
-$ cd get-started-experiments
-$ virtualenv .venv
-$ . .venv/bin/activate
-$ python -m pip install -r requirements.txt
-```
-
-### 📀 Get the data set
-
-The repository we cloned doesn't contain the dataset. In order to get the
-dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
-in DVC repositories to update the missing data dependencies.
-
-```dvc
-$ dvc pull
-```
-
-Then we extract this file that contains labeled images.
-
-```dvc
-$ tar -xvzf data/images.tar.gz --directory data/
-```
-
-The repository already contains the necessary configuration to run the
-experiments. If you would like to learn how to configure a project to run DVC
-experiments, please refer to the last section.
-
-</details>
-
-## 👟 Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
-experiments. By _ephemeral_ we mean the experiments can be run without
-committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment are tracked by DVC and persisted on demand.
-
-Running the experiment with default project settings requires only the command:
-
-```dvc
-$ dvc exp run
-...
-Reproduced experiment(s): exp-7683f
-Experiment results have been applied to your workspace.
-...
-```
-
-It runs the specified command that writes the metrics values to `metrics.json`.
-
-<details>
-
-### 📜 If you used `dvc repro` before
-
-Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may already be using `dvc repro`.
-
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
-pipeline.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit all to Git, it's better to
-use `dvc exp run`. It allows to change the parameters quickly, can track the
-history of artifacts and has facilities to compare these experiments easily.
-
-`dvc repro` is still available to run the pipeline when these extra features are
-not needed.
-
-</details>
-
-## 🧥 Running the experiment by setting parameters
-
-Now let's do some more experimentation.
-
-DVC allows to update the parameters defined in the pipeline without modifying
-the files manually. We use this feature to set the convolutional units in
-`train.py`.
-
-```dvc
-$ dvc exp run --set-param model.conv_units=24
-...
-Reproduced experiment(s): exp-6c06d
-Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
-```
-
-When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
-can see the effect of it by looking at the diff.
-
-```dvc
-$ git diff params.yaml
-```
-
-```git
--model:
--  conv_units: 16
-+model:
-+  conv_units: 24
-```
-
-## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
-
-Instead of running the experiments one-by-one, we can define them to run in a
-batch. This is especially handy when you have long running experiments.
-
-We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter.
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-$ dvc exp run --queue -S model.conv_units=64
-Queued experiment '30eb9b2' for future execution.
-$ dvc exp run --queue -S model.conv_units=128
-Queued experiment 'ac66940' for future execution.
-$ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.
-```
-
-Next, run all (`--run-all`) queued experiments in parallel. You can specify the
-number of parallel processes using `--jobs`:
-
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
-
-## ↔️ Comparing experiments
-
-The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
-
-```dvc
-$ dvc exp show
-```
-
-![](/img/start-dvc-exp-show-210704.png)
-
-By default it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
-hide the timestamp column with `--include-metrics`, `--include-params`, or
-`--no-timestamp` options of the command, respectively.
-
-```dvc
-$ dvc exp show --no-timestamp \
-  --include-params model.conv_units --include-metrics acc
-```
-
-![](/img/start-dvc-exp-show-no-timestamp-210704.png)
-
-## 🔏 Persisting experiments
-
-After selecting an experiment from the table, you can commit the hyperparameters
-and other dependencies that produced this successful experiment to your Git
-history.
-
-`dvc exp apply` brings back all specific artifacts and parameters from the
-experiment to the <abbr>workspace</abbr>.
-
-```dvc
-$ dvc exp apply exp-cb13f
-Changes for experiment 'exp-cb13f' have been applied to your current workspace.
-```
-
-We can see the changes in the repository and commit them to Git.
-
-```dvc
-$ git diff
-$ git add .
-$ git commit -m "Successful experiment"
-```
-
-It may also be desirable to commit a particular experiment to a Git branch
-directly, without bringing to the workspace.
-
-```dvc
-$ dvc exp branch exp-05e87 "cnn-256"
-Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
-To switch to the new branch run:
-
-        git checkout cnn-256
-```
-
-You can then checkout and continue from working this branch as usual.
-
-## 📛 Note on experiment names
-
-When you create an experiment, DVC generates a hash value from the contents of
-the experiment. This is shown when you use `--queue` option, e.g.,
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-```
-
-After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-`, and can be set via
-`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value as _queued experiment_:
-
-```dvc
-$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
-Queued experiment '86bd8f9' for future execution.
-```
-
-In `dvc exp show` you can see both of these names:
-
-```dvc
-$ dvc exp show --no-pager --no-timestamp \
-      --include-metrics loss --include-params model.conv_units
-
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ Experiment              ┃ loss    ┃ model.conv_units ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.23534 │ 64               │
-│ 3973b6b                 │ -       │ 16               │
-│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
-│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
-│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
-│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
-│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
-│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
-│ └── *86bd8f9            │ -       │ 512              │
-└─────────────────────────┴─────────┴──────────────────┘
-```
-
-When an experiment is not run yet, only the former hash value is shown.
-
-You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
-running the experiment with the name starting with `exp-`, or the name you have
-supplied with `dvc exp run --name`.
-
-## ⏲ Preparing a project for DVC experiments
-
-At the beginning of this document, we assumed that there is already a configured
-DVC project to simplify the introduction. DVC experiments are a feature added in
-DVC 2.0 and requires a DVC pipeline defined in the project. In this section
-we'll show how to configure a project to run DVC experiments.
-
-Please refer to [install](/doc/install) if DVC is not installed in your system.
-
-If DVC is not initialized before in the project, you can do so by:
-
-```dvc
-$ dvc init
-```
-
-DVC also requires commands to be run and their dependencies to be defined as
-stages. We use `dvc stage add` to add a stage and set its dependencies.
-
-```dvc
-$ dvc stage add -n train \
-                -p model.conv_units \
-                -p train.epochs \
-                -d data/images \
-                -m metrics.json \
-                python3 src/train.py
-```
-
-The command tells DVC to create an experiment named `train`, and that for any
-change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
-experiment using `src/train.py` that produces a new `metrics.json` file.
-
-Note that the parameters (added with `-p`) are in the default parameters file
-`params.yaml` and used in the code as normal, by reading the file. DVC only
-tracks the changes and updates them with `--set-param`.
-
-DVC is ready to run the experiments now!
-
-## 🪐 Go Further
-
-There are many other features of `dvc exp`, like cleaning up the unused
-experiments, sharing them without committing into Git or getting differences
-between two experiments.
-
-Please see the section on
-[Experiment Management](/doc/user-guide/experiment-management) in the User's
-Guide or `dvc exp` and subcommands in the Command Reference.

From 4a6cba7343b06aba611abf623332b450e5615ea6 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 16 Jul 2021 19:56:07 +0300
Subject: [PATCH 20/89] renamed experiments trail alt-3 and modified the
 sidebar

---
 content/docs/sidebar.json                         | 15 ++-------------
 .../{experiments-3.md => experiments.md}          |  0
 2 files changed, 2 insertions(+), 13 deletions(-)
 rename content/docs/start/experiments-trail/{experiments-3.md => experiments.md} (100%)

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index b3db277a97..2f3513226f 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -34,18 +34,6 @@
       "katacoda": "https://katacoda.com/dvc/courses/get-started"
     },
     "children": [
-      {
-        "slug": "experiments-trail/experiments-1",
-        "label": "Experiments Trail (Alternative 1)"
-      },
-      {
-        "slug": "experiments-trail/experiments-2",
-        "label": "Experiments Trail (Alternative 2)"
-      },
-      {
-        "slug": "experiments-trail/experiments-3",
-        "label": "Experiments Trail (Alternative 3)"
-      },
       {
         "slug": "data-and-model-versioning",
         "tutorials": {
@@ -72,7 +60,8 @@
         }
       },
       {
-        "slug": "experiments",
+        "slug": "experiments-trail/experiments",
+        "label": "Experiments Trail",
         "tutorials": {
           "katacoda": "https://katacoda.com/dvc/courses/get-started/experiments"
         }
diff --git a/content/docs/start/experiments-trail/experiments-3.md b/content/docs/start/experiments-trail/experiments.md
similarity index 100%
rename from content/docs/start/experiments-trail/experiments-3.md
rename to content/docs/start/experiments-trail/experiments.md

From 3b8cbe160710bcd367e9a851e4cd1dae6d32f3b7 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 20 Jul 2021 19:22:18 +0300
Subject: [PATCH 21/89] minor changes for experiment commands

---
 .../start/experiments-trail/experiments.md    | 19 ++++++++-----------
 1 file changed, 8 insertions(+), 11 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 46bbfcf116..a5505aa3f5 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -32,7 +32,7 @@ Please clone the project and create a virtual environment.
 > rest of your system. This prevents version conflicts.
 
 ```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
+$ git clone https://github.com/iterative/get-started-experiments -b get-started
 $ cd get-started-experiments
 $ virtualenv .venv
 $ . .venv/bin/activate
@@ -113,7 +113,7 @@ Running the experiment with default project settings requires only the command:
 ```dvc
 $ dvc exp run
 ...
-Reproduced experiment(s): exp-7683f
+Reproduced experiment(s): exp-b28f0
 Experiment results have been applied to your workspace.
 ...
 ```
@@ -153,12 +153,9 @@ the files manually. We use this feature to set the convolutional units in
 ```dvc
 $ dvc exp run --set-param model.conv_units=24
 ...
-Reproduced experiment(s): exp-6c06d
+Reproduced experiment(s): exp-7b56f
 Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
+...
 ```
 
 When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
@@ -185,13 +182,13 @@ also use `-S` (`--set-param`) to set a value for the parameter.
 
 ```dvc
 $ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
+Queued experiment '3cac8c6' for future execution.
 $ dvc exp run --queue -S model.conv_units=64
-Queued experiment '30eb9b2' for future execution.
+Queued experiment '23660b6' for future execution.
 $ dvc exp run --queue -S model.conv_units=128
-Queued experiment 'ac66940' for future execution.
+Queued experiment '6591a57' for future execution.
 $ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.
+Queued experiment '9109ea9' for future execution.
 ```
 
 Next, run all (`--run-all`) queued experiments in parallel. You can specify the

From 4c6b54d11ba7f019f79b634f685e76be8b881570 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 22 Jul 2021 14:56:12 +0300
Subject: [PATCH 22/89] updated the experiments  and removed some text

---
 .../start/experiments-trail/experiments.md    | 65 ++++++++++++-------
 1 file changed, 43 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index a5505aa3f5..ab29543112 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -49,23 +49,16 @@ in DVC repositories to update the missing data dependencies.
 $ dvc pull
 ```
 
-Then we extract this file that contains labeled images.
-
-```dvc
-$ tar -xvzf data/images.tar.gz --directory data/
-```
-
 The repository already contains the necessary configuration to run the
-experiments. If you would like to learn how to configure a project to run DVC
-experiments, please refer to the last section.
+experiments.
 
 <details>
 
 ## ⏲ Preparing a project for DVC experiments
 
 In this document we assume that there is already a configured DVC project to
-simplify the introduction. DVC experiments are a feature added in DVC 2.0 and
-requires a DVC pipeline defined in the project.
+simplify the introduction. DVC experiments require a DVC pipeline defined in the
+project.
 
 Please refer to [install](/doc/install) if DVC is not installed in your system.
 
@@ -91,22 +84,20 @@ The command tells DVC to create an experiment named `train`, and that for any
 change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
 experiment using `src/train.py` that produces a new `metrics.json` file.
 
-Note that the parameters (added with `-p`) are in the default parameters file
-`params.yaml` and used in the code as normal, by reading the file. DVC only
-tracks the changes and updates them with `--set-param`. For other files that
-contain the parameters, DVC expects the filename to be provided similar to
-`-p myparams.yaml:epochs`.
+You can get more information on [pipelines], and [parameters] in other sections
+of this guide.
 
-DVC is ready to run the experiments now!
+[pipelines]: /doc/start/data-pipelines
+[parameters]: /doc/start/metrics-parameters-plots
 
 </details>
 
 ## 👟 Running the experiment with default parameters
 
-The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
-experiments. By _ephemeral_ we mean the experiments can be run without
-committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment are tracked by DVC and persisted on demand.
+The purpose of `dvc exp` subcommands is to run the pipeline for experiments
+without committing parameter and dependency changes to Git. Instead the
+artifacts produced for each experiment are tracked by DVC and persisted on
+demand.
 
 Running the experiment with default project settings requires only the command:
 
@@ -172,6 +163,8 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
+<details>
+
 ## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
@@ -198,6 +191,8 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
+</details>
+
 ## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
@@ -208,7 +203,20 @@ parameters and metrics produced in experiments in a nicely formatted table.
 $ dvc exp show
 ```
 
-![](/img/start-dvc-exp-show-210704.png)
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**    ┃ white:**Created**┃    yellow:**loss** ┃    yellow:**acc** ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 05:14 PM     │ 0.23146 │ 0.9145 │ 10           │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 05:14 PM     │ 0.25231 │ 0.9102 │ 10           │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 04:46 PM     │ 0.23687 │ 0.9167 │ 10           │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 04:46 PM     │ 0.24459 │ 0.9134 │ 10           │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 03:35 PM     │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
+└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
+```
 
 By default it shows all the parameters and the metrics with the timestamp. If
 you have large number of parameters, metrics or experiments, this may lead to a
@@ -221,7 +229,20 @@ $ dvc exp show --no-timestamp \
   --include-params model.conv_units --include-metrics acc
 ```
 
-![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃    yellow:**acc** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.9151 │ 24               │
+│ 7317bc6                 │      - │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 0.9145 │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 0.9102 │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 0.9167 │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 0.9134 │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 0.9151 │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 0.9152 │ 16               │
+└─────────────────────────┴────────┴──────────────────┘
+```
 
 ## 🔏 Persisting experiments
 

From a2063ccc5e5c93c25aca927894c6ff2bb82a6075 Mon Sep 17 00:00:00 2001
From: "github@emresult.com" <github@emresult.com>
Date: Wed, 28 Jul 2021 14:35:30 +0000
Subject: [PATCH 23/89] Updated and simplified initial paragraphs

---
 .../docs/start/experiments-trail/experiments.md | 17 ++++++-----------
 1 file changed, 6 insertions(+), 11 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index ab29543112..9e17d22eb9 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -4,17 +4,12 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
-will explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
+<abbr>Experiments</abbr> grow rapidly in number in ML projects. DVC can track
+these experiments, list their most relevant parameters and metrics, and commit
+only the ones that we need to Git.
+
+In this section, we will explore the basic features of DVC experiment management
+with [`get-started-experiments`][gse] project.
 
 [gse]: https://github.com/iterative/get-started-experiments
 

From 7a6a70b6570f3149fd416a644a7285629b2384a2 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Fri, 30 Jul 2021 14:21:47 +0300
Subject: [PATCH 24/89] updated the details section scope to hide all
 installation info

---
 content/docs/start/experiments-trail/experiments.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 9e17d22eb9..1d3bc71f09 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -13,6 +13,8 @@ with [`get-started-experiments`][gse] project.
 
 [gse]: https://github.com/iterative/get-started-experiments
 
+<details>
+
 ## ⚙️ Installing the Example Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
@@ -47,8 +49,6 @@ $ dvc pull
 The repository already contains the necessary configuration to run the
 experiments.
 
-<details>
-
 ## ⏲ Preparing a project for DVC experiments
 
 In this document we assume that there is already a configured DVC project to

From e07584c88eb67271f7096ba230b1b7067ad3c42a Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 30 Jul 2021 14:45:53 +0300
Subject: [PATCH 25/89] moved params diff explanation to hidden section + minor
 edits

---
 .../start/experiments-trail/experiments.md    | 19 +++++++++++++------
 1 file changed, 13 insertions(+), 6 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 1d3bc71f09..080ba99177 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -4,9 +4,9 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-<abbr>Experiments</abbr> grow rapidly in number in ML projects. DVC can track
-these experiments, list their most relevant parameters and metrics, and commit
-only the ones that we need to Git.
+In machine learning projects, number of <abbr>experiments</abbr> grow rapidly.
+DVC can track these experiments, list their most relevant parameters and
+metrics, and commit only the ones that we need to Git.
 
 In this section, we will explore the basic features of DVC experiment management
 with [`get-started-experiments`][gse] project.
@@ -144,8 +144,13 @@ Experiment results have been applied to your workspace.
 ...
 ```
 
-When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
-can see the effect of it by looking at the diff.
+<details>
+
+### How DVC updates the parameters?
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file.
+(Default: `params.yaml`) We can see the effect of DVC updating the parameters by
+looking at the diff.
 
 ```dvc
 $ git diff params.yaml
@@ -158,9 +163,11 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
+</details>
+
 <details>
 
-## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
+## 👟👟 Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.

From cb777d35b982cef5c6837dd1eccfc235b9bbf183 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 10:52:17 +0300
Subject: [PATCH 26/89] replaced some emoji

---
 content/docs/start/experiments-trail/experiments.md | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 080ba99177..09999c083d 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -21,7 +21,7 @@ These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### 👥 Clone the project and create virtual environment
+### ⚡ Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -36,7 +36,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### 📀 Get the data set
+### ✅ Get the data set
 
 The repository we cloned doesn't contain the dataset. In order to get the
 dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
@@ -49,7 +49,7 @@ $ dvc pull
 The repository already contains the necessary configuration to run the
 experiments.
 
-## ⏲ Preparing a project for DVC experiments
+## 💡 Preparing a project for DVC experiments
 
 In this document we assume that there is already a configured DVC project to
 simplify the introduction. DVC experiments require a DVC pipeline defined in the
@@ -108,7 +108,7 @@ It runs the specified command that writes the metrics values to `metrics.json`.
 
 <details>
 
-### 📜 If you used `dvc repro` before
+### 📖 If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -128,7 +128,7 @@ not needed.
 
 </details>
 
-## 🧥 Running the experiment by setting parameters
+## ⏲ Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -328,7 +328,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## 🪐 Go Further
+## ⭐ Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From a1e6b6b4a8f4659fff931e97d9a4ff7b316facbb Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 10:54:16 +0300
Subject: [PATCH 27/89] removed the "note on experiments names" section

---
 .../start/experiments-trail/experiments.md    | 47 -------------------
 1 file changed, 47 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 09999c083d..1c8e3019b6 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -281,53 +281,6 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## 📛 Note on experiment names
-
-When you create an experiment, DVC generates a hash value from the contents of
-the experiment. This is shown when you use `--queue` option, e.g.,
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-```
-
-After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-`, and can be set via
-`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value as _queued experiment_:
-
-```dvc
-$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
-Queued experiment '86bd8f9' for future execution.
-```
-
-In `dvc exp show` you can see both of these names:
-
-```dvc
-$ dvc exp show --no-pager --no-timestamp \
-      --include-metrics loss --include-params model.conv_units
-
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ Experiment              ┃ loss    ┃ model.conv_units ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.23534 │ 64               │
-│ 3973b6b                 │ -       │ 16               │
-│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
-│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
-│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
-│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
-│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
-│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
-│ └── *86bd8f9            │ -       │ 512              │
-└─────────────────────────┴─────────┴──────────────────┘
-```
-
-When an experiment is not run yet, only the former hash value is shown.
-
-You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
-running the experiment with the name starting with `exp-`, or the name you have
-supplied with `dvc exp run --name`.
-
 ## ⭐ Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused

From c10457fd3e462c77555e56c9c1628ca340bd9e82 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 10:55:08 +0300
Subject: [PATCH 28/89] removed "how dvc updates parameters" section

---
 .../start/experiments-trail/experiments.md    | 21 -------------------
 1 file changed, 21 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 1c8e3019b6..fd710b30e5 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -146,27 +146,6 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-### How DVC updates the parameters?
-
-When you run `dvc exp run` with `--set-param`, it updates the parameter file.
-(Default: `params.yaml`) We can see the effect of DVC updating the parameters by
-looking at the diff.
-
-```dvc
-$ git diff params.yaml
-```
-
-```git
--model:
--  conv_units: 16
-+model:
-+  conv_units: 24
-```
-
-</details>
-
-<details>
-
 ## 👟👟 Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a

From aa30fdf4258de740b69ea0479f0e6959c1f10f4c Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 11:02:44 +0300
Subject: [PATCH 29/89] removed dvc exp apply

---
 .../start/experiments-trail/experiments.md    | 30 ++++---------------
 1 file changed, 5 insertions(+), 25 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index fd710b30e5..7572b25eaf 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -8,8 +8,8 @@ In machine learning projects, number of <abbr>experiments</abbr> grow rapidly.
 DVC can track these experiments, list their most relevant parameters and
 metrics, and commit only the ones that we need to Git.
 
-In this section, we will explore the basic features of DVC experiment management
-with [`get-started-experiments`][gse] project.
+In this section, we explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
 [gse]: https://github.com/iterative/get-started-experiments
 
@@ -80,7 +80,7 @@ change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
 experiment using `src/train.py` that produces a new `metrics.json` file.
 
 You can get more information on [pipelines], and [parameters] in other sections
-of this guide.
+of the documentation.
 
 [pipelines]: /doc/start/data-pipelines
 [parameters]: /doc/start/metrics-parameters-plots
@@ -227,28 +227,8 @@ $ dvc exp show --no-timestamp \
 
 ## 🔏 Persisting experiments
 
-After selecting an experiment from the table, you can commit the hyperparameters
-and other dependencies that produced this successful experiment to your Git
-history.
-
-`dvc exp apply` brings back all specific artifacts and parameters from the
-experiment to the <abbr>workspace</abbr>.
-
-```dvc
-$ dvc exp apply exp-cb13f
-Changes for experiment 'exp-cb13f' have been applied to your current workspace.
-```
-
-We can see the changes in the repository and commit them to Git.
-
-```dvc
-$ git diff
-$ git add .
-$ git commit -m "Successful experiment"
-```
-
-It may also be desirable to commit a particular experiment to a Git branch
-directly, without bringing to the workspace.
+After selecting an experiment from the table, you can create a Git branch that
+contains the experiment with all its related files.
 
 ```dvc
 $ dvc exp branch exp-05e87 "cnn-256"

From a8f0741fd58ba284eab0d19e9abf1051d6dc8208 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 20 Aug 2021 13:24:46 +0300
Subject: [PATCH 30/89] removed screenshots

---
 static/img/start-dvc-exp-show-210704.png       | Bin 218492 -> 0 bytes
 .../start-dvc-exp-show-no-timestamp-210704.png | Bin 125016 -> 0 bytes
 2 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 static/img/start-dvc-exp-show-210704.png
 delete mode 100644 static/img/start-dvc-exp-show-no-timestamp-210704.png

diff --git a/static/img/start-dvc-exp-show-210704.png b/static/img/start-dvc-exp-show-210704.png
deleted file mode 100644
index 478f10608954f5b38302a3a9bbed42d8b2fad56e..0000000000000000000000000000000000000000
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From 51afaf5d6d18c32662eb126fb2c6eb5b14253bb4 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 20 Aug 2021 14:22:59 +0300
Subject: [PATCH 31/89] edits for clarification

---
 .../start/experiments-trail/experiments.md    | 58 ++++++++++---------
 1 file changed, 31 insertions(+), 27 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 7572b25eaf..1e2eb91cfc 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -38,9 +38,8 @@ $ python -m pip install -r requirements.txt
 
 ### ✅ Get the data set
 
-The repository we cloned doesn't contain the dataset. In order to get the
-dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
-in DVC repositories to update the missing data dependencies.
+The repository we cloned doesn't contain the dataset. We use `dvc pull` to
+update the missing data files.
 
 ```dvc
 $ dvc pull
@@ -51,11 +50,11 @@ experiments.
 
 ## 💡 Preparing a project for DVC experiments
 
-In this document we assume that there is already a configured DVC project to
-simplify the introduction. DVC experiments require a DVC pipeline defined in the
-project.
+If DVC is not installed to the system, please refer to [install](/doc/install).
 
-Please refer to [install](/doc/install) if DVC is not installed in your system.
+In this getting started page, we assume that there is already a configured DVC
+project to simplify the introduction. DVC experiments require a DVC pipeline
+defined in the project.
 
 If DVC is not initialized before in the project, you can do so by:
 
@@ -75,12 +74,13 @@ $ dvc stage add -n train \
                 python3 src/train.py
 ```
 
-The command tells DVC to create an experiment named `train`, and that for any
-change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
-experiment using `src/train.py` that produces a new `metrics.json` file.
+The command tells DVC to create an experiment named `train`, and for any change
+in `data/images/` directory, `model.conv_units` or `train.epochs` parameters, we
+(re)run an experiment using `src/train.py` that produces a new `metrics.json`
+file.
 
-You can get more information on [pipelines], and [parameters] in other sections
-of the documentation.
+You can learn more about [pipelines], and [parameters] in other sections of the
+documentation.
 
 [pipelines]: /doc/start/data-pipelines
 [parameters]: /doc/start/metrics-parameters-plots
@@ -89,12 +89,12 @@ of the documentation.
 
 ## 👟 Running the experiment with default parameters
 
-The purpose of `dvc exp` subcommands is to run the pipeline for experiments
-without committing parameter and dependency changes to Git. Instead the
-artifacts produced for each experiment are tracked by DVC and persisted on
-demand.
+The purpose of `dvc exp` subcommands is to run the experiments without
+committing parameter and dependency changes to Git. The artifacts like models,
+metrics produced by each experiment are tracked by DVC and persisted on demand.
 
-Running the experiment with default project settings requires only the command:
+Running the experiment with the default project settings requires only the
+command:
 
 ```dvc
 $ dvc exp run
@@ -104,7 +104,12 @@ Experiment results have been applied to your workspace.
 ...
 ```
 
-It runs the specified command that writes the metrics values to `metrics.json`.
+It runs the specified command (`python train.py`) in `dvc.yaml`. That command
+writes the metrics values to `metrics.json`.
+
+This experiment is then associated with the values found in parameters file
+(`params.yaml`), and other dependencies (`data/images/`) with these produced
+metrics.
 
 <details>
 
@@ -113,15 +118,14 @@ It runs the specified command that writes the metrics values to `metrics.json`.
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
 
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
-pipeline.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit all to Git, it's better to
-use `dvc exp run`. It allows to change the parameters quickly, can track the
-history of artifacts and has facilities to compare these experiments easily.
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. We use `dvc repro` to run the
+pipeline as found in the <abbr>workspace</abbr>. All the parameters and
+dependencies are retrieved from the current workspace. It doesn't use any
+special objects to track the experiments or associate parameters with metrics.
+When you have large number of experiments that you don't want to commit all to
+Git, it's better to use `dvc exp run`. It allows to change the parameters
+quickly, can track the history of artifacts and has facilities to compare these
+experiments easily.
 
 `dvc repro` is still available to run the pipeline when these extra features are
 not needed.

From 96406ec9fcca886d79769a13a6ca950e3ad7c7e1 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:17:27 +0300
Subject: [PATCH 32/89] revised the doc per reviews

---
 .../start/experiments-trail/experiments.md    | 65 ++++---------------
 1 file changed, 14 insertions(+), 51 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 1e2eb91cfc..cc5a8b0baa 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -4,9 +4,10 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-In machine learning projects, number of <abbr>experiments</abbr> grow rapidly.
-DVC can track these experiments, list their most relevant parameters and
-metrics, and commit only the ones that we need to Git.
+In machine learning projects, the number of <abbr>experiments</abbr> grows
+rapidly. DVC can track these experiments, list and compare their most relevant
+parameters and metrics, navigate among them, and commit only the ones that we
+need to Git.
 
 In this section, we explore the basic features of DVC experiment management with
 [`get-started-experiments`][gse] project.
@@ -15,7 +16,7 @@ In this section, we explore the basic features of DVC experiment management with
 
 <details>
 
-## ⚙️ Installing the Example Project
+### ⚙️ Installing the Example Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
@@ -25,8 +26,8 @@ the requirements.
 
 Please clone the project and create a virtual environment.
 
-> We create a virtual environment to keep the libraries we use isolated from the
-> rest of your system. This prevents version conflicts.
+> We strongly recommend to create a virtual environment to keep the libraries we
+> use isolated from the rest of your system. This prevents version conflicts.
 
 ```dvc
 $ git clone https://github.com/iterative/get-started-experiments -b get-started
@@ -48,43 +49,6 @@ $ dvc pull
 The repository already contains the necessary configuration to run the
 experiments.
 
-## 💡 Preparing a project for DVC experiments
-
-If DVC is not installed to the system, please refer to [install](/doc/install).
-
-In this getting started page, we assume that there is already a configured DVC
-project to simplify the introduction. DVC experiments require a DVC pipeline
-defined in the project.
-
-If DVC is not initialized before in the project, you can do so by:
-
-```dvc
-$ dvc init
-```
-
-DVC also requires commands to be run and their dependencies to be defined as
-stages. We use `dvc stage add` to add a stage and set its dependencies.
-
-```dvc
-$ dvc stage add -n train \
-                -p model.conv_units \
-                -p train.epochs \
-                -d data/images \
-                -m metrics.json \
-                python3 src/train.py
-```
-
-The command tells DVC to create an experiment named `train`, and for any change
-in `data/images/` directory, `model.conv_units` or `train.epochs` parameters, we
-(re)run an experiment using `src/train.py` that produces a new `metrics.json`
-file.
-
-You can learn more about [pipelines], and [parameters] in other sections of the
-documentation.
-
-[pipelines]: /doc/start/data-pipelines
-[parameters]: /doc/start/metrics-parameters-plots
-
 </details>
 
 ## 👟 Running the experiment with default parameters
@@ -118,18 +82,16 @@ metrics.
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
 
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. We use `dvc repro` to run the
-pipeline as found in the <abbr>workspace</abbr>. All the parameters and
-dependencies are retrieved from the current workspace. It doesn't use any
-special objects to track the experiments or associate parameters with metrics.
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments or associate parameters
+with metrics.
+
 When you have large number of experiments that you don't want to commit all to
 Git, it's better to use `dvc exp run`. It allows to change the parameters
 quickly, can track the history of artifacts and has facilities to compare these
 experiments easily.
 
-`dvc repro` is still available to run the pipeline when these extra features are
-not needed.
-
 </details>
 
 ## ⏲ Running the experiment by setting parameters
@@ -242,7 +204,8 @@ To switch to the new branch run:
         git checkout cnn-256
 ```
 
-You can then checkout and continue from working this branch as usual.
+You can then checkout and continue working from this branch, or merge the branch
+your `main` branch with usual Git commands. .
 
 ## ⭐ Go Further
 

From 543596ef9384db2c0d1a0a67d47a12373f2cc1a4 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:30:21 +0300
Subject: [PATCH 33/89] Update
 content/docs/start/experiments-trail/experiments.md

Co-authored-by: Julie <43496356+julieg18@users.noreply.github.com>
---
 content/docs/start/experiments-trail/experiments.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index cc5a8b0baa..36c77e9554 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -152,7 +152,7 @@ $ dvc exp show
 
 ```dvctable
 ┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ white:**Experiment**    ┃ white:**Created**┃    yellow:**loss** ┃    yellow:**acc** ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
 ┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
 │ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
 │ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │

From b4fc360f2e22ce568405fa9c9881fdf6309b929b Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:41:51 +0300
Subject: [PATCH 34/89] minor edits

---
 content/docs/start/experiments-trail/experiments.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 36c77e9554..92ac9a275b 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -165,7 +165,7 @@ $ dvc exp show
 └─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
 ```
 
-By default it shows all the parameters and the metrics with the timestamp. If
+By default, it shows all the parameters and the metrics with the timestamp. If
 you have large number of parameters, metrics or experiments, this may lead to a
 cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
@@ -193,7 +193,8 @@ $ dvc exp show --no-timestamp \
 
 ## 🔏 Persisting experiments
 
-After selecting an experiment from the table, you can create a Git branch that
+After selecting an experiment from the table, it's possible to apply the
+experiment results to your workspace, or you can create a Git branch that
 contains the experiment with all its related files.
 
 ```dvc

From cadf03a0d294ea9f1929d8896f92fec91aa4f2b7 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:45:18 +0300
Subject: [PATCH 35/89] some emoji changes

---
 content/docs/start/experiments-trail/experiments.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 92ac9a275b..73622b84d7 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -51,7 +51,7 @@ experiments.
 
 </details>
 
-## 👟 Running the experiment with default parameters
+## ⚙️ Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the experiments without
 committing parameter and dependency changes to Git. The artifacts like models,
@@ -112,7 +112,7 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-## 👟👟 Run multiple experiments in parallel
+## ⚙️⚙️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -140,7 +140,7 @@ $ dvc exp run --run-all --jobs 2
 
 </details>
 
-## ↔️ Comparing experiments
+## 🙏️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the

From 9dde3f7209f3e7e65f3942596ea9c403c40cdf19 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:00:03 +0300
Subject: [PATCH 36/89] put the video

---
 content/docs/start/experiments-trail/experiments.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 73622b84d7..600e06b9e0 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -9,6 +9,8 @@ rapidly. DVC can track these experiments, list and compare their most relevant
 parameters and metrics, navigate among them, and commit only the ones that we
 need to Git.
 
+https://youtu.be/FHQq_zZz5ms
+
 In this section, we explore the basic features of DVC experiment management with
 [`get-started-experiments`][gse] project.
 

From 9a56f80a4188fc4ad43db586a1ad20a0c51deb5c Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:01:22 +0300
Subject: [PATCH 37/89] replaced older gs:experiments with the trail doc

---
 content/docs/sidebar.json                     |   4 +-
 .../start/experiments-trail/experiments.md    | 221 -----------
 content/docs/start/experiments.md             | 359 +++++++-----------
 3 files changed, 145 insertions(+), 439 deletions(-)
 delete mode 100644 content/docs/start/experiments-trail/experiments.md

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index 2f3513226f..e30a8bfb81 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -60,8 +60,8 @@
         }
       },
       {
-        "slug": "experiments-trail/experiments",
-        "label": "Experiments Trail",
+        "slug": "experiments",
+        "label": "Experiments",
         "tutorials": {
           "katacoda": "https://katacoda.com/dvc/courses/get-started/experiments"
         }
diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
deleted file mode 100644
index 600e06b9e0..0000000000
--- a/content/docs/start/experiments-trail/experiments.md
+++ /dev/null
@@ -1,221 +0,0 @@
----
-title: 'Get Started: Experiments'
----
-
-# Get Started with Experiments
-
-In machine learning projects, the number of <abbr>experiments</abbr> grows
-rapidly. DVC can track these experiments, list and compare their most relevant
-parameters and metrics, navigate among them, and commit only the ones that we
-need to Git.
-
-https://youtu.be/FHQq_zZz5ms
-
-In this section, we explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
-
-[gse]: https://github.com/iterative/get-started-experiments
-
-<details>
-
-### ⚙️ Installing the Example Project
-
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
-
-### ⚡ Clone the project and create virtual environment
-
-Please clone the project and create a virtual environment.
-
-> We strongly recommend to create a virtual environment to keep the libraries we
-> use isolated from the rest of your system. This prevents version conflicts.
-
-```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b get-started
-$ cd get-started-experiments
-$ virtualenv .venv
-$ . .venv/bin/activate
-$ python -m pip install -r requirements.txt
-```
-
-### ✅ Get the data set
-
-The repository we cloned doesn't contain the dataset. We use `dvc pull` to
-update the missing data files.
-
-```dvc
-$ dvc pull
-```
-
-The repository already contains the necessary configuration to run the
-experiments.
-
-</details>
-
-## ⚙️ Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to run the experiments without
-committing parameter and dependency changes to Git. The artifacts like models,
-metrics produced by each experiment are tracked by DVC and persisted on demand.
-
-Running the experiment with the default project settings requires only the
-command:
-
-```dvc
-$ dvc exp run
-...
-Reproduced experiment(s): exp-b28f0
-Experiment results have been applied to your workspace.
-...
-```
-
-It runs the specified command (`python train.py`) in `dvc.yaml`. That command
-writes the metrics values to `metrics.json`.
-
-This experiment is then associated with the values found in parameters file
-(`params.yaml`), and other dependencies (`data/images/`) with these produced
-metrics.
-
-<details>
-
-### 📖 If you used `dvc repro` before
-
-Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may already be using `dvc repro`.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments or associate parameters
-with metrics.
-
-When you have large number of experiments that you don't want to commit all to
-Git, it's better to use `dvc exp run`. It allows to change the parameters
-quickly, can track the history of artifacts and has facilities to compare these
-experiments easily.
-
-</details>
-
-## ⏲ Running the experiment by setting parameters
-
-Now let's do some more experimentation.
-
-DVC allows to update the parameters defined in the pipeline without modifying
-the files manually. We use this feature to set the convolutional units in
-`train.py`.
-
-```dvc
-$ dvc exp run --set-param model.conv_units=24
-...
-Reproduced experiment(s): exp-7b56f
-Experiment results have been applied to your workspace.
-...
-```
-
-<details>
-
-## ⚙️⚙️ Run multiple experiments in parallel
-
-Instead of running the experiments one-by-one, we can define them to run in a
-batch. This is especially handy when you have long running experiments.
-
-We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter.
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '3cac8c6' for future execution.
-$ dvc exp run --queue -S model.conv_units=64
-Queued experiment '23660b6' for future execution.
-$ dvc exp run --queue -S model.conv_units=128
-Queued experiment '6591a57' for future execution.
-$ dvc exp run --queue -S model.conv_units=256
-Queued experiment '9109ea9' for future execution.
-```
-
-Next, run all (`--run-all`) queued experiments in parallel. You can specify the
-number of parallel processes using `--jobs`:
-
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
-
-</details>
-
-## 🙏️ Comparing experiments
-
-The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
-
-```dvc
-$ dvc exp show
-```
-
-```dvctable
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
-│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
-│ ├── e2647ef [exp-ee8a4] │ 05:14 PM     │ 0.23146 │ 0.9145 │ 10           │ 64               │
-│ ├── 15c9451 [exp-a9be6] │ 05:14 PM     │ 0.25231 │ 0.9102 │ 10           │ 32               │
-│ ├── 9c32227 [exp-17dd9] │ 04:46 PM     │ 0.23687 │ 0.9167 │ 10           │ 256              │
-│ ├── 8a9cb15 [exp-29d93] │ 04:46 PM     │ 0.24459 │ 0.9134 │ 10           │ 128              │
-│ ├── dfc536f [exp-a1bd9] │ 03:35 PM     │ 0.23508 │ 0.9151 │ 10           │ 24               │
-│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
-└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
-```
-
-By default, it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
-hide the timestamp column with `--include-metrics`, `--include-params`, or
-`--no-timestamp` options of the command, respectively.
-
-```dvc
-$ dvc exp show --no-timestamp \
-  --include-params model.conv_units --include-metrics acc
-```
-
-```dvctable
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ white:**Experiment**              ┃    yellow:**acc** ┃ blue:**model.conv_units** ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.9151 │ 24               │
-│ 7317bc6                 │      - │ 16               │
-│ ├── e2647ef [exp-ee8a4] │ 0.9145 │ 64               │
-│ ├── 15c9451 [exp-a9be6] │ 0.9102 │ 32               │
-│ ├── 9c32227 [exp-17dd9] │ 0.9167 │ 256              │
-│ ├── 8a9cb15 [exp-29d93] │ 0.9134 │ 128              │
-│ ├── dfc536f [exp-a1bd9] │ 0.9151 │ 24               │
-│ └── 1a1d858 [exp-6dccf] │ 0.9152 │ 16               │
-└─────────────────────────┴────────┴──────────────────┘
-```
-
-## 🔏 Persisting experiments
-
-After selecting an experiment from the table, it's possible to apply the
-experiment results to your workspace, or you can create a Git branch that
-contains the experiment with all its related files.
-
-```dvc
-$ dvc exp branch exp-05e87 "cnn-256"
-Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
-To switch to the new branch run:
-
-        git checkout cnn-256
-```
-
-You can then checkout and continue working from this branch, or merge the branch
-your `main` branch with usual Git commands. .
-
-## ⭐ Go Further
-
-There are many other features of `dvc exp`, like cleaning up the unused
-experiments, sharing them without committing into Git or getting differences
-between two experiments.
-
-Please see the section on
-[Experiment Management](/doc/user-guide/experiment-management) in the User's
-Guide or `dvc exp` and subcommands in the Command Reference.
diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 09bd680eee..600e06b9e0 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -2,293 +2,220 @@
 title: 'Get Started: Experiments'
 ---
 
-# Get Started: Experiments
+# Get Started with Experiments
 
-_New in DVC 2.0_
-
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-> 📖 See [Experiment Management](/doc/user-guide/experiment-management) for more
-> information on DVC's approach.
+In machine learning projects, the number of <abbr>experiments</abbr> grows
+rapidly. DVC can track these experiments, list and compare their most relevant
+parameters and metrics, navigate among them, and commit only the ones that we
+need to Git.
 
 https://youtu.be/FHQq_zZz5ms
 
-## Running experiments
+In this section, we explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). Let's further
-increase the number of features in the `featurize` stage to see how it compares.
-
-`dvc exp run` makes it easy to change <abbr>hyperparameters</abbr> and run a new
-experiment:
-
-```dvc
-$ dvc exp run --set-param featurize.max_features=3000
-```
+[gse]: https://github.com/iterative/get-started-experiments
 
 <details>
 
-### 💡 Expand to see what happens under the hood.
-
-`dvc exp run` is similar to `dvc repro` but with some added conveniences for
-running experiments. The `--set-param` (or `-S`) flag sets the values for
-<abbr>parameters<abbr> as a shortcut for editing `params.yaml`.
+### ⚙️ Installing the Example Project
 
-Check that the `featurize.max_features` value has been updated in `params.yaml`:
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
 
-```git
- featurize:
--  max_features: 1500
-+  max_features: 3000
-```
-
-Any edits to <abbr>dependencies</abbr> (parameters or source code) will be
-reflected in the experiment run.
+### ⚡ Clone the project and create virtual environment
 
-</details>
+Please clone the project and create a virtual environment.
 
-`dvc exp diff` compares experiments:
+> We strongly recommend to create a virtual environment to keep the libraries we
+> use isolated from the rest of your system. This prevents version conflicts.
 
 ```dvc
-$ dvc exp diff
-Path         Metric    Value    Change
-scores.json  avg_prec  0.56191  0.009322
-scores.json  roc_auc   0.93345  0.018087
-
-Path         Param                   Value    Change
-params.yaml  featurize.max_features  3000     1500
+$ git clone https://github.com/iterative/get-started-experiments -b get-started
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
 ```
 
-## Queueing experiments
+### ✅ Get the data set
 
-So far, we have been tuning the `featurize` stage, but there are also parameters
-for the `train` stage (which trains a
-[random forest classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)).
-
-These are the `train` parameters from `params.yaml`:
-
-```yaml
-train:
-  seed: 20170428
-  n_est: 50
-  min_split: 2
-```
-
-Let's set up experiments with different hyperparameters. We can use the
-`--queue` flag to define all the combinations we want to try without executing
-anything (yet):
+The repository we cloned doesn't contain the dataset. We use `dvc pull` to
+update the missing data files.
 
 ```dvc
-$ dvc exp run --queue -S train.min_split=8
-Queued experiment 'd3f6d1e' for future execution.
-$ dvc exp run --queue -S train.min_split=64
-Queued experiment 'f1810e0' for future execution.
-$ dvc exp run --queue -S train.min_split=2 -S train.n_est=100
-Queued experiment '7323ea2' for future execution.
-$ dvc exp run --queue -S train.min_split=8 -S train.n_est=100
-Queued experiment 'c605382' for future execution.
-$ dvc exp run --queue -S train.min_split=64 -S train.n_est=100
-Queued experiment '0cdee86' for future execution.
+$ dvc pull
 ```
 
-Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+The repository already contains the necessary configuration to run the
+experiments.
 
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
+</details>
 
-## Comparing many experiments
+## ⚙️ Running the experiment with default parameters
 
-To compare all of these experiments, we need more than `diff`. `dvc exp show`
-compares any number of experiments in one table:
+The purpose of `dvc exp` subcommands is to run the experiments without
+committing parameter and dependency changes to Git. The artifacts like models,
+metrics produced by each experiment are tracked by DVC and persisted on demand.
 
-```dvc
-$ dvc exp show --no-timestamp \
-               --include-params train.n_est,train.min_split
-```
+Running the experiment with the default project settings requires only the
+command:
 
-```dvctable
-┏━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment**    ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**     │  **0.56191** │ **0.93345** │ **50**         │ **2**               │
-│ **master**        │  **0.55259** │ **0.91536** │ **50**         │ **2**               │
-│ ├── exp-bfe64 │  0.57833 │ 0.95555 │ 50         │ 8               │
-│ ├── exp-b8082 │  0.59806 │ 0.95287 │ 50         │ 64              │
-│ ├── exp-c7250 │  0.58876 │ 0.94524 │ 100        │ 2               │
-│ ├── exp-b9cd4 │  0.57953 │ 0.95732 │ 100        │ 8               │
-│ ├── exp-98a96 │  0.60405 │  0.9608 │ 100        │ 64              │
-│ └── exp-ad5b1 │  0.56191 │ 0.93345 │ 50         │ 2               │
-└───────────────┴──────────┴─────────┴────────────┴─────────────────┘
+```dvc
+$ dvc exp run
+...
+Reproduced experiment(s): exp-b28f0
+Experiment results have been applied to your workspace.
+...
 ```
 
-Each experiment is given an arbitrary name by default (although we can specify
-one with `dvc exp run -n`.) We can see that `exp-98a96` performed best among
-both of our metrics, with 100 estimators and a minimum of 64 samples to split a
-node.
-
-> See `dvc exp show --help` for more info on its options.
-
-## Persisting experiments
-
-Now that we know the best parameters, let's keep that experiment and ignore the
-rest.
+It runs the specified command (`python train.py`) in `dvc.yaml`. That command
+writes the metrics values to `metrics.json`.
 
-`dvc exp apply` rolls back the <abbr>workspace<abbr> to the specified
-experiment:
-
-```dvc
-$ dvc exp apply exp-98a96
-Changes for experiment 'exp-98a96' have been applied to your workspace.
-```
+This experiment is then associated with the values found in parameters file
+(`params.yaml`), and other dependencies (`data/images/`) with these produced
+metrics.
 
 <details>
 
-### 💡 Expand to see what happens under the hood.
+### 📖 If you used `dvc repro` before
 
-`dvc exp apply` is similar to `dvc checkout`, but works with experiments
-instead. DVC tracks everything in the pipeline for each experiment (parameters,
-metrics, dependencies, and outputs), retrieving things later as needed.
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may already be using `dvc repro`.
 
-Check that `scores.json` reflects the metrics in the table above:
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments or associate parameters
+with metrics.
 
-```json
-{ "avg_prec": 0.6040544652105823, "roc_auc": 0.9608017142900953 }
-```
+When you have large number of experiments that you don't want to commit all to
+Git, it's better to use `dvc exp run`. It allows to change the parameters
+quickly, can track the history of artifacts and has facilities to compare these
+experiments easily.
 
 </details>
 
-Once an experiment has been applied to the workspace, it is no different from
-reproducing the result without `dvc exp run`. Let's make it persistent in our
-regular pipeline by committing it in our Git branch:
-
-```dvc
-$ git add dvc.lock params.yaml prc.json roc.json scores.json
-$ git commit -a -m "Preserve best random forest experiment"
-```
+## ⏲ Running the experiment by setting parameters
 
-## Sharing experiments
+Now let's do some more experimentation.
 
-After committing the best experiments to our Git branch, we can
-[store and share](/doc/start/data-and-model-versioning#storing-and-sharing) them
-remotely like any other iteration of the pipeline.
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
 
 ```dvc
-dvc push
-git push
+$ dvc exp run --set-param model.conv_units=24
+...
+Reproduced experiment(s): exp-7b56f
+Experiment results have been applied to your workspace.
+...
 ```
 
 <details>
 
-### 💡 Important information on storing experiments remotely.
+## ⚙️⚙️ Run multiple experiments in parallel
 
-The commands in this section require both a `dvc remote default` and a
-[Git remote](https://git-scm.com/book/en/v2/Git-Basics-Working-with-Remotes). A
-DVC remote stores the experiment data, and a Git remote stores the code,
-parameters, and other metadata associated with the experiment. DVC supports
-various types of remote storage (local file system, SSH, Amazon S3, Google Cloud
-Storage, HTTP, HDFS, etc.). The Git remote is often a central Git server
-(GitHub, GitLab, BitBucket, etc.).
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
 
-</details>
-
-Experiments that have not been made persistent will not be stored or shared
-remotely through `dvc push` or `git push`.
-
-`dvc exp push` enables storing and sharing any experiment remotely.
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter.
 
 ```dvc
-$ dvc exp push gitremote exp-bfe64
-Pushed experiment 'exp-bfe64' to Git remote 'gitremote'.
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '3cac8c6' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '23660b6' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment '6591a57' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '9109ea9' for future execution.
 ```
 
-`dvc exp list` shows all experiments that have been saved.
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
 
 ```dvc
-$ dvc exp list gitremote --all
-72ed9cd:
-        exp-bfe64
+$ dvc exp run --run-all --jobs 2
 ```
 
-`dvc exp pull` retrieves the experiment from a Git remote.
+</details>
 
-```dvc
-$ dvc exp pull gitremote exp-bfe64
-Pulled experiment 'exp-bfe64' from Git remote 'gitremote'.
-```
+## 🙏️ Comparing experiments
 
-> All these commands take a Git remote as an argument. A `dvc remote default` is
-> also required to share the experiment data.
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
 
-## Cleaning up
+```dvc
+$ dvc exp show
+```
 
-Let's take another look at the experiments table:
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 05:14 PM     │ 0.23146 │ 0.9145 │ 10           │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 05:14 PM     │ 0.25231 │ 0.9102 │ 10           │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 04:46 PM     │ 0.23687 │ 0.9167 │ 10           │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 04:46 PM     │ 0.24459 │ 0.9134 │ 10           │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 03:35 PM     │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
+└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
+```
+
+By default, it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
 
 ```dvc
 $ dvc exp show --no-timestamp \
-               --include-params train.n_est,train.min_split
+  --include-params model.conv_units --include-metrics acc
 ```
 
 ```dvctable
-┏━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment** ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**  │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **master**     │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-└────────────┴──────────┴─────────┴────────────┴─────────────────┘
-```
-
-Where did all the experiments go? By default, `dvc exp show` only shows
-experiments since the last commit, but don't worry. The experiments remain
-<abbr>cached</abbr> and can be shown or applied. For example, use `-n` to show
-experiments from the previous _n_ commits:
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃    yellow:**acc** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.9151 │ 24               │
+│ 7317bc6                 │      - │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 0.9145 │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 0.9102 │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 0.9167 │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 0.9134 │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 0.9151 │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 0.9152 │ 16               │
+└─────────────────────────┴────────┴──────────────────┘
+```
+
+## 🔏 Persisting experiments
+
+After selecting an experiment from the table, it's possible to apply the
+experiment results to your workspace, or you can create a Git branch that
+contains the experiment with all its related files.
 
 ```dvc
-$ dvc exp show -n 2 --no-timestamp \
-                    --include-params train.n_est,train.min_split
-```
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
 
-```dvctable
-┏━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment**    ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**     │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **master**        │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **64d74b2**       │  **0.55259** │ **0.91536** │ **50**         │ **2**               │
-│ ├── exp-bfe64 │  0.57833 │ 0.95555 │ 50         │ 8               │
-│ ├── exp-b8082 │  0.59806 │ 0.95287 │ 50         │ 64              │
-│ ├── exp-c7250 │  0.58876 │ 0.94524 │ 100        │ 2               │
-│ ├── exp-98a96 │  0.60405 │  0.9608 │ 100        │ 64              │
-│ ├── exp-b9cd4 │  0.57953 │ 0.95732 │ 100        │ 8               │
-│ └── exp-ad5b1 │  0.56191 │ 0.93345 │ 50         │ 2               │
-└───────────────┴──────────┴─────────┴────────────┴─────────────────┘
+        git checkout cnn-256
 ```
 
-Eventually, old experiments may clutter the experiments table.
-
-`dvc exp gc` removes all references to old experiments:
+You can then checkout and continue working from this branch, or merge the branch
+your `main` branch with usual Git commands. .
 
-```dvc
-$ dvc exp gc --workspace
-$ dvc exp show -n 2 --no-timestamp \
-                    --include-params train.n_est,train.min_split
-```
+## ⭐ Go Further
 
-```dvctable
-┏━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment** ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**  │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **master**     │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **64d74b2**    │  **0.55259** │ **0.91536** │ **50**         │ **2**               │
-└────────────┴──────────┴─────────┴────────────┴─────────────────┘
-```
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
 
-> `dvc exp gc` only removes references to the experiments; not the cached
-> objects associated with them. To clean up the <abbr>cache</abbr>, use
-> `dvc gc`.
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From d1f929a45a2ca410994715fb8a5bed74dcba95cf Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:12:05 +0300
Subject: [PATCH 38/89] Removed emoji and moved persisting to details section

---
 content/docs/start/experiments.md | 26 +++++++++++++++-----------
 1 file changed, 15 insertions(+), 11 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 600e06b9e0..89b9d62847 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -18,13 +18,13 @@ In this section, we explore the basic features of DVC experiment management with
 
 <details>
 
-### ⚙️ Installing the Example Project
+### Installing the Example Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### ⚡ Clone the project and create virtual environment
+#### Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -39,7 +39,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### ✅ Get the data set
+#### Get the data set
 
 The repository we cloned doesn't contain the dataset. We use `dvc pull` to
 update the missing data files.
@@ -53,7 +53,7 @@ experiments.
 
 </details>
 
-## ⚙️ Running the experiment with default parameters
+## Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the experiments without
 committing parameter and dependency changes to Git. The artifacts like models,
@@ -79,7 +79,7 @@ metrics.
 
 <details>
 
-### 📖 If you used `dvc repro` before
+### If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -96,7 +96,7 @@ experiments easily.
 
 </details>
 
-## ⏲ Running the experiment by setting parameters
+## Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -114,7 +114,7 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-## ⚙️⚙️ Run multiple experiments in parallel
+### Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -142,7 +142,7 @@ $ dvc exp run --run-all --jobs 2
 
 </details>
 
-## 🙏️ Comparing experiments
+## Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -193,7 +193,9 @@ $ dvc exp show --no-timestamp \
 └─────────────────────────┴────────┴──────────────────┘
 ```
 
-## 🔏 Persisting experiments
+<details>
+
+### Persisting experiments
 
 After selecting an experiment from the table, it's possible to apply the
 experiment results to your workspace, or you can create a Git branch that
@@ -208,9 +210,11 @@ To switch to the new branch run:
 ```
 
 You can then checkout and continue working from this branch, or merge the branch
-your `main` branch with usual Git commands. .
+your `main` branch with usual Git commands.
+
+</details>
 
-## ⭐ Go Further
+## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From d085d77f7e530152a3ee901dc5e7841e9cf82c3e Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:24:56 +0300
Subject: [PATCH 39/89] added a sentence for data management

---
 content/docs/start/experiments.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 89b9d62847..8a66e66cec 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -41,8 +41,9 @@ $ python -m pip install -r requirements.txt
 
 #### Get the data set
 
-The repository we cloned doesn't contain the dataset. We use `dvc pull` to
-update the missing data files.
+The repository we cloned doesn't contain the dataset. Instead of storing the
+data in Git repository, we use DVC to retrieve from a shared data store. In this
+case, we use `dvc pull` to update the missing data files.
 
 ```dvc
 $ dvc pull

From 797fc1dafae662180698ad98aa8ab11935edd202 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Wed, 6 Oct 2021 14:12:15 +0300
Subject: [PATCH 40/89] added a brief `dvc exp show` after the first run.

---
 content/docs/start/experiments.md | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 8a66e66cec..d2de3621ec 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -78,6 +78,26 @@ This experiment is then associated with the values found in parameters file
 (`params.yaml`), and other dependencies (`data/images/`) with these produced
 metrics.
 
+You can review the experiment results with `dvc exp show` and see these metrics
+and results in a nicely formatted table:
+
+```dvc
+$ dvc exp show
+```
+
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ -            │ 0.23282 │ 0.9152 │ 10           │ 16               │
+│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
+│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
+└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
+```
+
+The `workspace` row in the table shows the results of the most recent experiment
+that's available in the <bbr>workspace</abbr>.
+
 <details>
 
 ### If you used `dvc repro` before

From 34c165f208a42ebedce6a88b673d8aa8b86a95bf Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Wed, 6 Oct 2021 14:16:25 +0300
Subject: [PATCH 41/89] added emoji to detail headers

---
 content/docs/start/experiments.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index d2de3621ec..3b47f8ca7a 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -18,7 +18,7 @@ In this section, we explore the basic features of DVC experiment management with
 
 <details>
 
-### Installing the Example Project
+### ⚙️ Installing the example project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
@@ -100,7 +100,7 @@ that's available in the <bbr>workspace</abbr>.
 
 <details>
 
-### If you used `dvc repro` before
+### ℹ️ If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -135,7 +135,7 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-### Run multiple experiments in parallel
+### ⚙️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -216,7 +216,7 @@ $ dvc exp show --no-timestamp \
 
 <details>
 
-### Persisting experiments
+### ✅ Persisting experiments
 
 After selecting an experiment from the table, it's possible to apply the
 experiment results to your workspace, or you can create a Git branch that

From 46411bf95fd706f56463ccf86755a2e22262bcf9 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Wed, 6 Oct 2021 14:26:44 +0300
Subject: [PATCH 42/89] added an initial text

---
 content/docs/start/experiments.md | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 3b47f8ca7a..9edbf6c8b3 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -56,9 +56,11 @@ experiments.
 
 ## Running the experiment with default parameters
 
-The purpose of `dvc exp` subcommands is to run the experiments without
-committing parameter and dependency changes to Git. The artifacts like models,
-metrics produced by each experiment are tracked by DVC and persisted on demand.
+The purpose of `dvc exp` subcommands is to let you run, capture, compare the
+machine learning experiments at once as you iterate on your code, data, and
+hyperparameters. The artifacts like models, metrics produced by each experiment
+are tracked by DVC and the associated parameters and metrics can be committed to
+Git as text files.
 
 Running the experiment with the default project settings requires only the
 command:

From 72cca7c4274e264e71d61bc90f32f19e1ec8b2e3 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Fri, 8 Oct 2021 16:44:36 +0300
Subject: [PATCH 43/89] some suggestions of Ivan applied.

---
 content/docs/start/experiments.md | 29 +++++++++++------------------
 1 file changed, 11 insertions(+), 18 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 9edbf6c8b3..1f3bf4f003 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -54,14 +54,6 @@ experiments.
 
 </details>
 
-## Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to let you run, capture, compare the
-machine learning experiments at once as you iterate on your code, data, and
-hyperparameters. The artifacts like models, metrics produced by each experiment
-are tracked by DVC and the associated parameters and metrics can be committed to
-Git as text files.
-
 Running the experiment with the default project settings requires only the
 command:
 
@@ -80,6 +72,12 @@ This experiment is then associated with the values found in parameters file
 (`params.yaml`), and other dependencies (`data/images/`) with these produced
 metrics.
 
+The purpose of `dvc exp` family of commands is to let you run, capture, compare
+the machine learning experiments at once as you iterate on your code, data,
+models, and hyperparameters. The artifacts like models, metrics produced by each
+experiment are tracked by DVC and the associated parameters and metrics can be
+committed to Git as text files.
+
 You can review the experiment results with `dvc exp show` and see these metrics
 and results in a nicely formatted table:
 
@@ -98,7 +96,10 @@ $ dvc exp show
 ```
 
 The `workspace` row in the table shows the results of the most recent experiment
-that's available in the <bbr>workspace</abbr>.
+that's available in the <bbr>workspace</abbr>. The table also shows each
+experiment in a separate row, along with the Git commit IDs they are attached
+to. We can see that the experiment we run has a name `exp-6dccf` and run from
+the commit ID `7317bc6`.
 
 <details>
 
@@ -119,8 +120,6 @@ experiments easily.
 
 </details>
 
-## Running the experiment by setting parameters
-
 Now let's do some more experimentation.
 
 DVC allows to update the parameters defined in the pipeline without modifying
@@ -165,7 +164,7 @@ $ dvc exp run --run-all --jobs 2
 
 </details>
 
-## Comparing experiments
+## Comparing and persisting experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -216,10 +215,6 @@ $ dvc exp show --no-timestamp \
 └─────────────────────────┴────────┴──────────────────┘
 ```
 
-<details>
-
-### ✅ Persisting experiments
-
 After selecting an experiment from the table, it's possible to apply the
 experiment results to your workspace, or you can create a Git branch that
 contains the experiment with all its related files.
@@ -235,8 +230,6 @@ To switch to the new branch run:
 You can then checkout and continue working from this branch, or merge the branch
 your `main` branch with usual Git commands.
 
-</details>
-
 ## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused

From dad083d1f5c95b49e77a7306173c9d0518e436f1 Mon Sep 17 00:00:00 2001
From: Emre Sahin <galaxy@emresult.com>
Date: Fri, 2 Jul 2021 14:27:46 +0300
Subject: [PATCH 44/89] experiments draft 1 moved to experiments-trail/

---
 .../start/experiments-trail/experiments-1.md  | 215 ++++++++++++++++++
 1 file changed, 215 insertions(+)
 create mode 100644 content/docs/start/experiments-trail/experiments-1.md

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
new file mode 100644
index 0000000000..a6a5d5aa79
--- /dev/null
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -0,0 +1,215 @@
+---
+title: 'Get Started: Experiments'
+---
+
+# Get Started with Experiments
+
+<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
+parameters to tune or other permutations of the code. We can organize such
+projects and keep only what we ultimately need with `dvc experiments`. DVC can
+track experiments for you so there's no need to commit each one to Git. This way
+your repo doesn't become polluted with all of them. You can discard experiments
+once they're no longer needed.
+
+Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
+[compare the changes](/doc/start/metrics-parameters-plots). Let's further
+increase the number of features in the `featurize` stage to see how it compares.
+<details>
+## Installing and Configuring the Project
+
+These commands are run in the
+[`get-started-experiments`](https://github.com/iterative/get-started-experiments)
+project. You can run the commands in this document after cloning the repository
+and installing the requirements.
+
+### Clone the project and create venv
+
+Please clone the project and create a virtual environment. 
+
+> We create a virtual environment to keep the libraries we use isolated from
+> the rest of your system. This prevents version conflicts.
+
+```dvc
+$ git clone https://github.com/iterative/get-started-experiments -b git-init
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
+```
+
+### Create the pipeline
+
+DVC tracks the dependencies across project elements with pipelines. Experiments
+also need a pipeline to run.  
+
+We create a two stage pipeline to expand the dataset from a `tar.gz` file
+to a directory and specify the training command to depend on dataset and a
+parameter, and produce a metrics file.
+
+```dvc
+$ dvc stage add -n expand \
+                -d data/fashion-mnist.tar.gz \
+                -o data/images \
+                tar xvzf data/fashion-mnist.tar.gz
+$ dvc stage add -n train \
+                -p conv_units \
+                -d data/images \
+                -m metrics.json \
+                python3 train.py 
+```
+
+### Get the data set
+
+The repository you cloned doesn't contain the dataset. DVC tracks the datafiles
+separately from the text files.  In order to get `fashion-mnist.tar.gz` from
+the `dataset-registry`, we ask DVC to pull the missing data files. 
+
+```dvc
+$ dvc pull
+```
+
+</details> ## Running experiments ### Running with default parameters
+
+The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+experiments. By _ephemeral_ we mean the experiments can be run without
+committing parameter and dependency changes to Git. Instead the artifacts
+produced for each experiment is tracked by DVC and persisted on demand. 
+
+Running the pipeline with default values requires only the command:
+
+``` dvc
+$ dvc exp run
+TK
+```
+
+It runs the pipeline starting from the basic dependencies and produces
+`metrics.json` file for the default state. 
+
+<details>
+
+### If you used `dvc repro` before
+
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may be used to `dvc repro`.
+
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the pipeline.
+
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace.
+It doesn't use any special objects to track the experiments.
+	 
+When you have large number of experiments that you don't want to commit into
+Git, it's better to use `dvc exp run`. It allows to change the parameters
+quickly, can track the history of artifacts and has facilities to compare
+these experiments easily.
+
+`dvc repro` is still available to run the pipeline that don't need these extra
+features. 
+ 
+</details>
+
+### Running by setting parameters
+
+Now let's do some more experimentation. 
+
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
+
+```dvc
+$ dvc exp run --set-param conv_units=24 
+TK
+```
+
+Note that the pipeline didn't run the earliest stage. Only the stages that
+depend on the updated parameter and subsequent stages are run. 
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file.
+We can see the effect of it by looking at the diff. 
+
+```dvc
+$ git diff params.yaml
+TK
+```
+
+### Run multiple experiments in parallel
+
+Instead of running the experiments one-by-one, we can define them first to run
+them in a batch. This is especially handy when you have long running
+experiments. 
+
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter. 
+
+``` dvc
+$ dvc exp run --queue -S conv_units=32
+$ dvc exp run --queue -S conv_units=64
+$ dvc exp run --queue -S conv_units=128
+$ dvc exp run --queue -S conv_units=256
+```
+
+Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+
+```dvc
+$ dvc exp run --run-all --jobs 2
+TK
+```
+
+## Comparing experiments
+
+The pipeline is run several times with different parameters. To compare all of
+these experiments, we use `dvc exp show`. This command presents the parameters
+and metrics produced in experiments in a nicely formatted table.
+
+```dvc
+$ dvc exp show
+```
+TK
+
+By default it shows all the parameters and the metrics along with the
+timestamp. If you have large number of parameters, metrics or experiments, this
+may lead to a cluttered view. You can limit the table to specific metrics, or
+parameters, or hide the timestamp column with `--include-metrics`,
+`--include-params`, or `--no-timestamp` options of the command, respectively.
+
+```dvc
+$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
+TK
+```
+
+## Persisting experiments
+
+After selecting a experiments from the table, you can commit the
+hyperparameters and other dependencies that produced this successful experiment
+to your Git history. 
+
+`dvc exp apply` brings back all specific artifacts and parameters from the
+experiment to the <abbr>workspace</abbr>.
+
+```dvc
+$ dvc exp apply 
+TK
+```
+
+We can see the changes in the repository and commit them to Git. 
+
+```dvc
+$ git diff
+$ git add .
+$ git commit -m "Successful experiment"
+```
+
+## Go Further
+
+You can continue to experiment with [the
+project](https://github.com/iterative/get-started-experiments).  Please see the
+`README.md` file of the project for these. Don't forget to [notify
+us](https://dvc.org/chat) if you happen to find good parameters.
+
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
+
+Please see the section on [Experiment
+Management](/doc/user-guide/experiment-management) in the User's Guide or `dvc
+exp` and subcommands in the Command Reference. 

From 7f768e228352a03d0e0ec233d10c819168537d95 Mon Sep 17 00:00:00 2001
From: Emre Sahin <galaxy@emresult.com>
Date: Fri, 2 Jul 2021 16:04:30 +0300
Subject: [PATCH 45/89] modifications for downloading the data and setting up
 the experiment manually

---
 .../start/experiments-trail/experiments-1.md  | 73 +++++++++++++------
 1 file changed, 51 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index a6a5d5aa79..c7ae612e28 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -14,13 +14,18 @@ once they're no longer needed.
 Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
 [compare the changes](/doc/start/metrics-parameters-plots). Let's further
 increase the number of features in the `featurize` stage to see how it compares.
+
+In this section, we will explore the basic features of DVC experiment
+management with `[get-started-experiments]` project. 
+
+get-started-experiments: https://github.com/iterative/get-started-experiments
+
 <details>
 ## Installing and Configuring the Project
 
-These commands are run in the
-[`get-started-experiments`](https://github.com/iterative/get-started-experiments)
-project. You can run the commands in this document after cloning the repository
-and installing the requirements.
+These commands are run in the `[get-started-experiments]` project. You can run
+the commands in this document after cloning the repository and installing the
+requirements.
 
 ### Clone the project and create venv
 
@@ -30,45 +35,69 @@ Please clone the project and create a virtual environment.
 > the rest of your system. This prevents version conflicts.
 
 ```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b git-init
+$ git clone https://github.com/iterative/get-started-experiments -b source-code
 $ cd get-started-experiments
 $ virtualenv .venv
 $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### Create the pipeline
+### Get the data set
+
+The repository you cloned doesn't contain the dataset. In order to get
+`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to
+download the missing data files.  `dvc get` is similar to `wget` but works with
+Git+DVC repositories to download binary files.
+
+```dvc
+$ dvc get https://github.com/iterative/dataset-registry \
+          fashion-mnist/images.tar.gz -o data/images.tar.gz
+```
+
+Then we extract this file that contains labeled images. 
+
+```dvc
+$ tar -xvzf data/images.tar.gz --directory data/
+``` 
+
+### Specifying the experiment
+
+We first initialize DVC inside the project to create an experiment.
+
+```dvc
+$ dvc init
+```
 
-DVC tracks the dependencies across project elements with pipelines. Experiments
-also need a pipeline to run.  
+DVC experiments are run by specifying their commands, outputs, parameters and
+dependencies. We add an experiment command by `dvc stage add`. 
 
-We create a two stage pipeline to expand the dataset from a `tar.gz` file
-to a directory and specify the training command to depend on dataset and a
-parameter, and produce a metrics file.
 
 ```dvc
-$ dvc stage add -n expand \
-                -d data/fashion-mnist.tar.gz \
-                -o data/images \
-                tar xvzf data/fashion-mnist.tar.gz
 $ dvc stage add -n train \
-                -p conv_units \
+                -p model.conv_units \
+                -p train.conv_units \
                 -d data/images \
                 -m metrics.json \
                 python3 train.py 
 ```
 
-### Get the data set
+The command tells DVC to create an experiment named `train`, with two
+parameters and a data dependency to `data/images`. The command produces
+`metrics.json` as a special type of output. 
 
-The repository you cloned doesn't contain the dataset. DVC tracks the datafiles
-separately from the text files.  In order to get `fashion-mnist.tar.gz` from
-the `dataset-registry`, we ask DVC to pull the missing data files. 
+DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
+artifacts. 
 
 ```dvc
-$ dvc pull
+$ git add dvc.yaml .gitignore
+$ git commit -m "added data and the experiment" 
 ```
 
-</details> ## Running experiments ### Running with default parameters
+</details>
+
+## Running experiments 
+
+### Running with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without

From 761c864352cc1261b15cdb72bf44566f2d3e32e0 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Sat, 3 Jul 2021 13:46:14 +0300
Subject: [PATCH 46/89] Fix project installation and commands

---
 .../start/experiments-trail/experiments-1.md  | 117 +++++++++---------
 1 file changed, 58 insertions(+), 59 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index c7ae612e28..08f7a9e7fb 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -15,8 +15,8 @@ Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
 [compare the changes](/doc/start/metrics-parameters-plots). Let's further
 increase the number of features in the `featurize` stage to see how it compares.
 
-In this section, we will explore the basic features of DVC experiment
-management with `[get-started-experiments]` project. 
+In this section, we will explore the basic features of DVC experiment management
+with `[get-started-experiments]` project.
 
 get-started-experiments: https://github.com/iterative/get-started-experiments
 
@@ -27,12 +27,12 @@ These commands are run in the `[get-started-experiments]` project. You can run
 the commands in this document after cloning the repository and installing the
 requirements.
 
-### Clone the project and create venv
+### Clone the project and create virtual environment
 
-Please clone the project and create a virtual environment. 
+Please clone the project and create a virtual environment.
 
-> We create a virtual environment to keep the libraries we use isolated from
-> the rest of your system. This prevents version conflicts.
+> We create a virtual environment to keep the libraries we use isolated from the
+> rest of your system. This prevents version conflicts.
 
 ```dvc
 $ git clone https://github.com/iterative/get-started-experiments -b source-code
@@ -45,20 +45,20 @@ $ python -m pip install -r requirements.txt
 ### Get the data set
 
 The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to
-download the missing data files.  `dvc get` is similar to `wget` but works with
-Git+DVC repositories to download binary files.
+`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to download
+the missing data files. `dvc get` is similar to `wget` but works with Git+DVC
+repositories to download binary files.
 
 ```dvc
 $ dvc get https://github.com/iterative/dataset-registry \
           fashion-mnist/images.tar.gz -o data/images.tar.gz
 ```
 
-Then we extract this file that contains labeled images. 
+Then we extract this file that contains labeled images.
 
 ```dvc
 $ tar -xvzf data/images.tar.gz --directory data/
-``` 
+```
 
 ### Specifying the experiment
 
@@ -69,50 +69,49 @@ $ dvc init
 ```
 
 DVC experiments are run by specifying their commands, outputs, parameters and
-dependencies. We add an experiment command by `dvc stage add`. 
-
+dependencies. We add an experiment command by `dvc stage add`.
 
 ```dvc
 $ dvc stage add -n train \
                 -p model.conv_units \
-                -p train.conv_units \
+                -p train.epochs \
                 -d data/images \
                 -m metrics.json \
-                python3 train.py 
+                python3 src/train.py
 ```
 
-The command tells DVC to create an experiment named `train`, with two
-parameters and a data dependency to `data/images`. The command produces
-`metrics.json` as a special type of output. 
+The command tells DVC to create an experiment named `train`, with two parameters
+and a data dependency to `data/images`. The command produces `metrics.json` as a
+special type of output.
 
 DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
-artifacts. 
+artifacts.
 
 ```dvc
 $ git add dvc.yaml .gitignore
-$ git commit -m "added data and the experiment" 
+$ git commit -m "added data and the experiment"
 ```
 
 </details>
 
-## Running experiments 
+## Running experiments
 
 ### Running with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment is tracked by DVC and persisted on demand. 
+produced for each experiment is tracked by DVC and persisted on demand.
 
 Running the pipeline with default values requires only the command:
 
-``` dvc
+```dvc
 $ dvc exp run
 TK
 ```
 
 It runs the pipeline starting from the basic dependencies and produces
-`metrics.json` file for the default state. 
+`metrics.json` file for the default state.
 
 <details>
 
@@ -121,40 +120,39 @@ It runs the pipeline starting from the basic dependencies and produces
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may be used to `dvc repro`.
 
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the pipeline.
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
+pipeline.
 
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace.
-It doesn't use any special objects to track the experiments.
-	 
-When you have large number of experiments that you don't want to commit into
-Git, it's better to use `dvc exp run`. It allows to change the parameters
-quickly, can track the history of artifacts and has facilities to compare
-these experiments easily.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments. When you have large
+number of experiments that you don't want to commit into Git, it's better to use
+`dvc exp run`. It allows to change the parameters quickly, can track the history
+of artifacts and has facilities to compare these experiments easily.
 
 `dvc repro` is still available to run the pipeline that don't need these extra
-features. 
- 
+features.
+
 </details>
 
 ### Running by setting parameters
 
-Now let's do some more experimentation. 
+Now let's do some more experimentation.
 
 DVC allows to update the parameters defined in the pipeline without modifying
 the files manually. We use this feature to set the convolutional units in
 `train.py`.
 
 ```dvc
-$ dvc exp run --set-param conv_units=24 
+$ dvc exp run --set-param conv_units=24
 TK
 ```
 
 Note that the pipeline didn't run the earliest stage. Only the stages that
-depend on the updated parameter and subsequent stages are run. 
+depend on the updated parameter and subsequent stages are run.
 
-When you run `dvc exp run` with `--set-param`, it updates the parameter file.
-We can see the effect of it by looking at the diff. 
+When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
+can see the effect of it by looking at the diff.
 
 ```dvc
 $ git diff params.yaml
@@ -165,12 +163,12 @@ TK
 
 Instead of running the experiments one-by-one, we can define them first to run
 them in a batch. This is especially handy when you have long running
-experiments. 
+experiments.
 
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter. 
+also use `-S` (`--set-param`) to set a value for the parameter.
 
-``` dvc
+```dvc
 $ dvc exp run --queue -S conv_units=32
 $ dvc exp run --queue -S conv_units=64
 $ dvc exp run --queue -S conv_units=128
@@ -193,13 +191,14 @@ and metrics produced in experiments in a nicely formatted table.
 ```dvc
 $ dvc exp show
 ```
+
 TK
 
-By default it shows all the parameters and the metrics along with the
-timestamp. If you have large number of parameters, metrics or experiments, this
-may lead to a cluttered view. You can limit the table to specific metrics, or
-parameters, or hide the timestamp column with `--include-metrics`,
-`--include-params`, or `--no-timestamp` options of the command, respectively.
+By default it shows all the parameters and the metrics along with the timestamp.
+If you have large number of parameters, metrics or experiments, this may lead to
+a cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
 
 ```dvc
 $ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
@@ -208,19 +207,19 @@ TK
 
 ## Persisting experiments
 
-After selecting a experiments from the table, you can commit the
-hyperparameters and other dependencies that produced this successful experiment
-to your Git history. 
+After selecting a experiments from the table, you can commit the hyperparameters
+and other dependencies that produced this successful experiment to your Git
+history.
 
 `dvc exp apply` brings back all specific artifacts and parameters from the
 experiment to the <abbr>workspace</abbr>.
 
 ```dvc
-$ dvc exp apply 
+$ dvc exp apply
 TK
 ```
 
-We can see the changes in the repository and commit them to Git. 
+We can see the changes in the repository and commit them to Git.
 
 ```dvc
 $ git diff
@@ -230,15 +229,15 @@ $ git commit -m "Successful experiment"
 
 ## Go Further
 
-You can continue to experiment with [the
-project](https://github.com/iterative/get-started-experiments).  Please see the
-`README.md` file of the project for these. Don't forget to [notify
-us](https://dvc.org/chat) if you happen to find good parameters.
+You can continue to experiment with
+[the project](https://github.com/iterative/get-started-experiments). Please see
+the `README.md` file of the project for these. Don't forget to
+[notify us](https://dvc.org/chat) if you happen to find good parameters.
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences
 between two experiments.
 
-Please see the section on [Experiment
-Management](/doc/user-guide/experiment-management) in the User's Guide or `dvc
-exp` and subcommands in the Command Reference. 
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From 506f0fa0bb925ca3e4548466bab85b5532157452 Mon Sep 17 00:00:00 2001
From: Emre Sahin <iex@redmi.emresahin.net>
Date: Mon, 5 Jul 2021 22:36:14 +0300
Subject: [PATCH 47/89] added second draft for experiments

---
 .../start/experiments-trail/experiments-2.md  | 228 ++++++++++++++++++
 1 file changed, 228 insertions(+)
 create mode 100644 content/docs/start/experiments-trail/experiments-2.md

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
new file mode 100644
index 0000000000..93d9250740
--- /dev/null
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -0,0 +1,228 @@
+---
+title: 'Get Started: Experiments'
+---
+
+# Get Started with Experiments
+
+<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
+parameters to tune or other permutations of the code. We can organize such
+projects and keep only what we ultimately need with `dvc experiments`. DVC can
+track experiments for you so there's no need to commit each one to Git. This way
+your repo doesn't become polluted with all of them. You can discard experiments
+once they're no longer needed.
+
+Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
+[compare the changes](/doc/start/metrics-parameters-plots). Let's further
+increase the number of features in the `featurize` stage to see how it compares.
+
+In this section, we will explore the basic features of DVC experiment management
+with `[get-started-experiments]` project.
+
+get-started-experiments: https://github.com/iterative/get-started-experiments
+
+## Installing and Configuring the Project
+
+These commands are run in the `[get-started-experiments]` project. You can run
+the commands in this document after cloning the repository and installing the
+requirements.
+
+### Clone the project and create virtual environment
+
+Please clone the project and create a virtual environment.
+
+> We create a virtual environment to keep the libraries we use isolated from the
+> rest of your system. This prevents version conflicts.
+
+```dvc
+$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
+```
+
+### Get the data set
+
+The repository you cloned doesn't contain the dataset. In order to get
+`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc pull` to update
+the missing data files. `dvc pull` is used in DVC repositories to update the missing data dependencies. 
+
+```dvc
+$ dvc pull
+```
+
+Then we extract this file that contains labeled images.
+
+```dvc
+$ tar -xvzf data/images.tar.gz --directory data/
+```
+
+</details>
+
+## Running experiments
+
+### Running with default parameters
+
+The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+experiments. By _ephemeral_ we mean the experiments can be run without
+committing parameter and dependency changes to Git. Instead the artifacts
+produced for each experiment is tracked by DVC and persisted on demand.
+
+Running the pipeline with default values requires only the command:
+
+```dvc
+$ dvc exp run
+TK
+```
+
+It runs the pipeline starting from the basic dependencies and produces
+`metrics.json` file for the default state.
+
+<details>
+
+### If you used `dvc repro` before
+
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may be used to `dvc repro`.
+
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
+pipeline.
+
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments. When you have large
+number of experiments that you don't want to commit into Git, it's better to use
+`dvc exp run`. It allows to change the parameters quickly, can track the history
+of artifacts and has facilities to compare these experiments easily.
+
+`dvc repro` is still available to run the pipeline that don't need these extra
+features.
+
+</details>
+
+### Running by setting parameters
+
+Now let's do some more experimentation.
+
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
+
+```dvc
+$ dvc exp run --set-param conv_units=24
+TK
+```
+
+Note that the pipeline didn't run the earliest stage. Only the stages that
+depend on the updated parameter and subsequent stages are run.
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
+can see the effect of it by looking at the diff.
+
+```dvc
+$ git diff params.yaml
+TK
+```
+
+### Run multiple experiments in parallel
+
+Instead of running the experiments one-by-one, we can define them first to run
+them in a batch. This is especially handy when you have long running
+experiments.
+
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter.
+
+```dvc
+$ dvc exp run --queue -S conv_units=32
+$ dvc exp run --queue -S conv_units=64
+$ dvc exp run --queue -S conv_units=128
+$ dvc exp run --queue -S conv_units=256
+```
+
+Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+
+```dvc
+$ dvc exp run --run-all --jobs 2
+TK
+```
+
+## Comparing experiments
+
+The pipeline is run several times with different parameters. To compare all of
+these experiments, we use `dvc exp show`. This command presents the parameters
+and metrics produced in experiments in a nicely formatted table.
+
+```dvc
+$ dvc exp show
+```
+
+TK
+
+By default it shows all the parameters and the metrics along with the timestamp.
+If you have large number of parameters, metrics or experiments, this may lead to
+a cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
+
+```dvc
+$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
+TK
+```
+
+## Persisting experiments
+
+After selecting a experiments from the table, you can commit the hyperparameters
+and other dependencies that produced this successful experiment to your Git
+history.
+
+`dvc exp apply` brings back all specific artifacts and parameters from the
+experiment to the <abbr>workspace</abbr>.
+
+```dvc
+$ dvc exp apply
+TK
+```
+
+We can see the changes in the repository and commit them to Git.
+
+```dvc
+$ git diff
+$ git add .
+$ git commit -m "Successful experiment"
+```
+
+### Preparing an experiments pipeline
+
+At the beginning of this document, we assumed that there is already a configured DVC project to simplify the introduction. DVC experiments are a feature added in DVC 2.0 and requires a DVC pipeline is defined in the project. In this section we'll show how to configure a project to run DVC experiments. You can get detailed information about these commands in other sections of DVC documentation.
+
+If DVC is not initialized before in the project, you can do so by:
+
+```dvc
+$ dvc init
+```
+
+DVC also requires commands to be run and their dependencies to be defined as stages. We use `dvc stage add` to add a stage and set its dependencies. 
+
+```dvc
+$ dvc stage add
+TK
+```
+
+Note that the parameters (added with `-p`) are in the default parameters file `params.yaml` and used in the code as normal, by reading the file. DVC only tracks the changes and updates them with `--set-param`. 
+
+
+## Go Further
+
+You can continue to experiment with
+[the project](https://github.com/iterative/get-started-experiments). Please see
+the `README.md` file of the project for these. Don't forget to
+[notify us](https://dvc.org/chat) if you happen to find good parameters.
+
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
+
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From e7c1127ba30f82d40d88c9f96b1e44e713c7a5b9 Mon Sep 17 00:00:00 2001
From: "restyled-io[bot]" <32688539+restyled-io[bot]@users.noreply.github.com>
Date: Mon, 5 Jul 2021 22:45:06 +0300
Subject: [PATCH 48/89] Restyled by prettier (#2608)

Co-authored-by: Restyled.io <commits@restyled.io>
---
 .../start/experiments-trail/experiments-2.md   | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 93d9250740..d42b924c4a 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -45,7 +45,8 @@ $ python -m pip install -r requirements.txt
 
 The repository you cloned doesn't contain the dataset. In order to get
 `fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc pull` to update
-the missing data files. `dvc pull` is used in DVC repositories to update the missing data dependencies. 
+the missing data files. `dvc pull` is used in DVC repositories to update the
+missing data dependencies.
 
 ```dvc
 $ dvc pull
@@ -194,7 +195,12 @@ $ git commit -m "Successful experiment"
 
 ### Preparing an experiments pipeline
 
-At the beginning of this document, we assumed that there is already a configured DVC project to simplify the introduction. DVC experiments are a feature added in DVC 2.0 and requires a DVC pipeline is defined in the project. In this section we'll show how to configure a project to run DVC experiments. You can get detailed information about these commands in other sections of DVC documentation.
+At the beginning of this document, we assumed that there is already a configured
+DVC project to simplify the introduction. DVC experiments are a feature added in
+DVC 2.0 and requires a DVC pipeline is defined in the project. In this section
+we'll show how to configure a project to run DVC experiments. You can get
+detailed information about these commands in other sections of DVC
+documentation.
 
 If DVC is not initialized before in the project, you can do so by:
 
@@ -202,15 +208,17 @@ If DVC is not initialized before in the project, you can do so by:
 $ dvc init
 ```
 
-DVC also requires commands to be run and their dependencies to be defined as stages. We use `dvc stage add` to add a stage and set its dependencies. 
+DVC also requires commands to be run and their dependencies to be defined as
+stages. We use `dvc stage add` to add a stage and set its dependencies.
 
 ```dvc
 $ dvc stage add
 TK
 ```
 
-Note that the parameters (added with `-p`) are in the default parameters file `params.yaml` and used in the code as normal, by reading the file. DVC only tracks the changes and updates them with `--set-param`. 
-
+Note that the parameters (added with `-p`) are in the default parameters file
+`params.yaml` and used in the code as normal, by reading the file. DVC only
+tracks the changes and updates them with `--set-param`.
 
 ## Go Further
 

From 05fef9e594f853f8099c12fb7c2be5219668be7d Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 00:13:27 +0300
Subject: [PATCH 49/89] Update version 1 by some command outputs

---
 .../start/experiments-trail/experiments-1.md  | 87 +++++++++++++------
 1 file changed, 62 insertions(+), 25 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 08f7a9e7fb..59da7fe053 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -68,6 +68,21 @@ We first initialize DVC inside the project to create an experiment.
 $ dvc init
 ```
 
+Now, we can add the dataset to the project:
+
+```dvc
+$ dvc add data/images
+```
+
+This creates a `data/images.dvc` file that contains all the relevant metadata of
+the directory. You can add and commit the corresponding `.dvc` file and changes
+in `.gitignore` that hides the `data/images/` directory from Git.
+
+```dvc
+$ git add data/.gitignore data/images.dvc
+$ git commit -m "Dataset added"
+```
+
 DVC experiments are run by specifying their commands, outputs, parameters and
 dependencies. We add an experiment command by `dvc stage add`.
 
@@ -92,22 +107,29 @@ $ git add dvc.yaml .gitignore
 $ git commit -m "added data and the experiment"
 ```
 
-</details>
+DVC is ready to run the experiments now!
 
-## Running experiments
+</details>
 
-### Running with default parameters
+## Running the experiment with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment is tracked by DVC and persisted on demand.
 
-Running the pipeline with default values requires only the command:
+Running the experiment with default hyperparameter values requires only the
+command:
 
 ```dvc
 $ dvc exp run
-TK
+...
+Reproduced experiment(s): exp-7683f
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
 ```
 
 It runs the pipeline starting from the basic dependencies and produces
@@ -135,7 +157,7 @@ features.
 
 </details>
 
-### Running by setting parameters
+## Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -144,22 +166,31 @@ the files manually. We use this feature to set the convolutional units in
 `train.py`.
 
 ```dvc
-$ dvc exp run --set-param conv_units=24
-TK
-```
+$ dvc exp run --set-param model.conv_units=24
+...
+Reproduced experiment(s): exp-6c06d
+Experiment results have been applied to your workspace.
 
-Note that the pipeline didn't run the earliest stage. Only the stages that
-depend on the updated parameter and subsequent stages are run.
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
+```
 
 When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
 can see the effect of it by looking at the diff.
 
 ```dvc
 $ git diff params.yaml
-TK
 ```
 
-### Run multiple experiments in parallel
+```git
+-model:
+-  conv_units: 16
++model:
++  conv_units: 24
+```
+
+## Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them first to run
 them in a batch. This is especially handy when you have long running
@@ -168,19 +199,22 @@ experiments.
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
 
-```dvc
-$ dvc exp run --queue -S conv_units=32
-$ dvc exp run --queue -S conv_units=64
-$ dvc exp run --queue -S conv_units=128
-$ dvc exp run --queue -S conv_units=256
-```
+````dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '30eb9b2' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment 'ac66940' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '8bb6049' for future execution.```
 
 Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
 TK
-```
+````
 
 ## Comparing experiments
 
@@ -227,12 +261,15 @@ $ git add .
 $ git commit -m "Successful experiment"
 ```
 
-## Go Further
+It may also be desirable to commit a particular experiment to a Git branch
+directly, without bringing to the workspace.
 
-You can continue to experiment with
-[the project](https://github.com/iterative/get-started-experiments). Please see
-the `README.md` file of the project for these. Don't forget to
-[notify us](https://dvc.org/chat) if you happen to find good parameters.
+```dvc
+$ dvc exp branch exp-
+TK
+```
+
+## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From e9d94c5c767299864c37f571d5d7bc2507d9397c Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 12:53:49 +0300
Subject: [PATCH 50/89] Added naming section and two screenshots to draft 1

---
 .../start/experiments-trail/experiments-1.md  |  78 +++++++++++++++---
 static/img/start-dvc-exp-show-210704.png      | Bin 0 -> 218492 bytes
 ...start-dvc-exp-show-no-timestamp-210704.png | Bin 0 -> 125016 bytes
 3 files changed, 67 insertions(+), 11 deletions(-)
 create mode 100644 static/img/start-dvc-exp-show-210704.png
 create mode 100644 static/img/start-dvc-exp-show-no-timestamp-210704.png

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 59da7fe053..b63f4f6de9 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -21,7 +21,8 @@ with `[get-started-experiments]` project.
 get-started-experiments: https://github.com/iterative/get-started-experiments
 
 <details>
-## Installing and Configuring the Project
+
+### Installing and Configuring the Project
 
 These commands are run in the `[get-started-experiments]` project. You can run
 the commands in this document after cloning the repository and installing the
@@ -116,7 +117,7 @@ DVC is ready to run the experiments now!
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment is tracked by DVC and persisted on demand.
+produced for each experiment are tracked by DVC and persisted on demand.
 
 Running the experiment with default hyperparameter values requires only the
 command:
@@ -207,15 +208,17 @@ Queued experiment '30eb9b2' for future execution.
 $ dvc exp run --queue -S model.conv_units=128
 Queued experiment 'ac66940' for future execution.
 $ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.```
+Queued experiment '8bb6049' for future execution.
+```
 
 Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
-TK
 ````
 
+It runs all the experiments with different processes.
+
 ## Comparing experiments
 
 The pipeline is run several times with different parameters. To compare all of
@@ -226,7 +229,7 @@ and metrics produced in experiments in a nicely formatted table.
 $ dvc exp show
 ```
 
-TK
+![](/img/start-dvc-exp-show-210704.png)
 
 By default it shows all the parameters and the metrics along with the timestamp.
 If you have large number of parameters, metrics or experiments, this may lead to
@@ -235,10 +238,11 @@ hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
 ```dvc
-$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
-TK
+$ dvc exp show --no-timestamp --include-params model.conv_units --include-metrics acc
 ```
 
+![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+
 ## Persisting experiments
 
 After selecting a experiments from the table, you can commit the hyperparameters
@@ -249,8 +253,8 @@ history.
 experiment to the <abbr>workspace</abbr>.
 
 ```dvc
-$ dvc exp apply
-TK
+$ dvc exp apply exp-cb13f
+Changes for experiment 'exp-cb13f' have been applied to your current workspace.
 ```
 
 We can see the changes in the repository and commit them to Git.
@@ -265,10 +269,62 @@ It may also be desirable to commit a particular experiment to a Git branch
 directly, without bringing to the workspace.
 
 ```dvc
-$ dvc exp branch exp-
-TK
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
+
+        git checkout cnn-256
 ```
 
+You can then checkout and continue from working this branch as usual.
+
+## A note on experiment names
+
+When you create an experiment, DVC generates a hash value from the contents of
+the experiment. This is shown when you use `--queue` option, e.g.,
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+```
+
+After _running_ the experiment, DVC uses another auto-generated name to refer to
+the experiment. Typically these start with `exp-` by default, and can be set via
+`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
+the name, you can see the hash value:
+
+```dvc
+$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
+Queued experiment '86bd8f9' for future execution.
+```
+
+In `dvc exp show` you can see both of these names:
+
+```dvc
+$ dvc exp show --no-pager --no-timestamp \
+      --include-metrics loss --include-params model.conv_units
+
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ Experiment              ┃ loss    ┃ model.conv_units ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.23534 │ 64               │
+│ 3973b6b                 │ -       │ 16               │
+│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
+│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
+│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
+│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
+│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
+│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
+│ └── *86bd8f9            │ -       │ 512              │
+└─────────────────────────┴─────────┴──────────────────┘
+```
+
+When an experiment is not run yet, only the former hash value is shown.
+
+You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
+running the experiment with the name starting with `exp-`, or the name you have
+supplied with `dvc exp run --name`.
+
 ## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
diff --git a/static/img/start-dvc-exp-show-210704.png b/static/img/start-dvc-exp-show-210704.png
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From 518cb574cbc1d379b7e98d25dc043052d44f8058 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 13:20:26 +0300
Subject: [PATCH 51/89] adding separate section for experiment preparation in
 draft 2

---
 .../start/experiments-trail/experiments-2.md  | 53 +++++++++++++------
 1 file changed, 37 insertions(+), 16 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index d42b924c4a..2fdc1e50b0 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -58,22 +58,30 @@ Then we extract this file that contains labeled images.
 $ tar -xvzf data/images.tar.gz --directory data/
 ```
 
-</details>
+The repository already contains the necessary configuration to run the
+experiments. If you would like to learn how to configure a project to run DVC
+experiments, please refer to the last section.
 
-## Running experiments
+</details>
 
-### Running with default parameters
+## Running the experiments with default parameters
 
 The purpose of `dvc exp` commands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment is tracked by DVC and persisted on demand.
+produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the pipeline with default values requires only the command:
+Running the experiments with default values requires only the command:
 
 ```dvc
 $ dvc exp run
-TK
+...
+Reproduced experiment(s): exp-7683f
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
 ```
 
 It runs the pipeline starting from the basic dependencies and produces
@@ -101,7 +109,7 @@ features.
 
 </details>
 
-### Running by setting parameters
+## Running the experiments by setting parameters
 
 Now let's do some more experimentation.
 
@@ -111,18 +119,27 @@ the files manually. We use this feature to set the convolutional units in
 
 ```dvc
 $ dvc exp run --set-param conv_units=24
-TK
-```
+...
+Reproduced experiment(s): exp-6c06d
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
 
-Note that the pipeline didn't run the earliest stage. Only the stages that
-depend on the updated parameter and subsequent stages are run.
+        dvc exp branch <exp>
+```
 
 When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
 can see the effect of it by looking at the diff.
 
 ```dvc
 $ git diff params.yaml
-TK
+```
+
+```git
+-model:
+-  conv_units: 16
++model:
++  conv_units: 24
 ```
 
 ### Run multiple experiments in parallel
@@ -135,10 +152,14 @@ We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
 
 ```dvc
-$ dvc exp run --queue -S conv_units=32
-$ dvc exp run --queue -S conv_units=64
-$ dvc exp run --queue -S conv_units=128
-$ dvc exp run --queue -S conv_units=256
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '30eb9b2' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment 'ac66940' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '8bb6049' for future execution.
 ```
 
 Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):

From 8e3f1867ac2d7a3ba23cc86cff5c3ca5380de39b Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 18:37:43 +0300
Subject: [PATCH 52/89] fixed link to the project and added some explanations
 to installation

---
 .../start/experiments-trail/experiments-1.md  | 36 +++++++++----------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index b63f4f6de9..da96512b54 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -12,21 +12,19 @@ your repo doesn't become polluted with all of them. You can discard experiments
 once they're no longer needed.
 
 Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). Let's further
-increase the number of features in the `featurize` stage to see how it compares.
+[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
+will explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
-In this section, we will explore the basic features of DVC experiment management
-with `[get-started-experiments]` project.
-
-get-started-experiments: https://github.com/iterative/get-started-experiments
+[gse]: https://github.com/iterative/get-started-experiments
 
 <details>
 
 ### Installing and Configuring the Project
 
-These commands are run in the `[get-started-experiments]` project. You can run
-the commands in this document after cloning the repository and installing the
-requirements.
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
 
 ### Clone the project and create virtual environment
 
@@ -46,8 +44,8 @@ $ python -m pip install -r requirements.txt
 ### Get the data set
 
 The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc get` to download
-the missing data files. `dvc get` is similar to `wget` but works with Git+DVC
+`fashion-mnist.tar.gz` from `dataset-registry`, we use `dvc get` to download the
+missing data files. `dvc get` is similar to `wget` but works with Git+DVC
 repositories to download binary files.
 
 ```dvc
@@ -61,7 +59,7 @@ Then we extract this file that contains labeled images.
 $ tar -xvzf data/images.tar.gz --directory data/
 ```
 
-### Specifying the experiment
+### Specify the experiment
 
 We first initialize DVC inside the project to create an experiment.
 
@@ -69,15 +67,15 @@ We first initialize DVC inside the project to create an experiment.
 $ dvc init
 ```
 
-Now, we can add the dataset to the project:
+Then we add the dataset to the project:
 
 ```dvc
 $ dvc add data/images
 ```
 
 This creates a `data/images.dvc` file that contains all the relevant metadata of
-the directory. You can add and commit the corresponding `.dvc` file and changes
-in `.gitignore` that hides the `data/images/` directory from Git.
+the directory. You can add and commit `data/images.dvc` file, and changes in
+`.gitignore` that hides the `data/images/` directory from Git.
 
 ```dvc
 $ git add data/.gitignore data/images.dvc
@@ -85,7 +83,7 @@ $ git commit -m "Dataset added"
 ```
 
 DVC experiments are run by specifying their commands, outputs, parameters and
-dependencies. We add an experiment command by `dvc stage add`.
+dependencies. We specify an experiment command by `dvc stage add`.
 
 ```dvc
 $ dvc stage add -n train \
@@ -97,8 +95,10 @@ $ dvc stage add -n train \
 ```
 
 The command tells DVC to create an experiment named `train`, with two parameters
-and a data dependency to `data/images`. The command produces `metrics.json` as a
-special type of output.
+and a dependency to `data/images`. The command produces `metrics.json` as a
+special type of output. Basically it tells DVC that for any change in
+`data/images/`, `model.conv_units` or `train.epochs`, we run an experiment using
+`src/train.py` that produces a new `metrics.json` file.
 
 DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
 artifacts.

From 14518f9fb56b97773cce9f370811d64a3b49a679 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 18:45:40 +0300
Subject: [PATCH 53/89] some minor edits in draft 1

---
 .../docs/start/experiments-trail/experiments-1.md  | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index da96512b54..41179baa9a 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -114,7 +114,7 @@ DVC is ready to run the experiments now!
 
 ## Running the experiment with default parameters
 
-The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
@@ -141,7 +141,7 @@ It runs the pipeline starting from the basic dependencies and produces
 ### If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may be used to `dvc repro`.
+have a DVC project, you may already be using `dvc repro`.
 
 In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
 pipeline.
@@ -149,12 +149,12 @@ pipeline.
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
 All the parameters and dependencies are retrieved from the current workspace. It
 doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit into Git, it's better to use
-`dvc exp run`. It allows to change the parameters quickly, can track the history
-of artifacts and has facilities to compare these experiments easily.
+number of experiments that you don't want to commit all to Git, it's better to
+use `dvc exp run`. It allows to change the parameters quickly, can track the
+history of artifacts and has facilities to compare these experiments easily.
 
-`dvc repro` is still available to run the pipeline that don't need these extra
-features.
+`dvc repro` is still available to run the pipeline when these extra features are
+not needed.
 
 </details>
 

From ac242222f4ef4dc8515fd32420e5c4ad8ff91cdd Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 19:19:11 +0300
Subject: [PATCH 54/89] minor edits in pipeline explanation

---
 .../start/experiments-trail/experiments-1.md  | 40 +++++++++----------
 1 file changed, 19 insertions(+), 21 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 41179baa9a..c0d2dde4dd 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -94,11 +94,9 @@ $ dvc stage add -n train \
                 python3 src/train.py
 ```
 
-The command tells DVC to create an experiment named `train`, with two parameters
-and a dependency to `data/images`. The command produces `metrics.json` as a
-special type of output. Basically it tells DVC that for any change in
-`data/images/`, `model.conv_units` or `train.epochs`, we run an experiment using
-`src/train.py` that produces a new `metrics.json` file.
+The command tells DVC to create an experiment named `train`, and that for any
+change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
+experiment using `src/train.py` that produces a new `metrics.json` file.
 
 DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
 artifacts.
@@ -193,14 +191,13 @@ $ git diff params.yaml
 
 ## Run multiple experiments in parallel
 
-Instead of running the experiments one-by-one, we can define them first to run
-them in a batch. This is especially handy when you have long running
-experiments.
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
 
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
 
-````dvc
+```dvc
 $ dvc exp run --queue -S model.conv_units=32
 Queued experiment '6518f17' for future execution.
 $ dvc exp run --queue -S model.conv_units=64
@@ -215,15 +212,15 @@ Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
-````
+```
 
-It runs all the experiments with different processes.
+It runs all the experiments, with the specified number of processes in parallel.
 
 ## Comparing experiments
 
-The pipeline is run several times with different parameters. To compare all of
-these experiments, we use `dvc exp show`. This command presents the parameters
-and metrics produced in experiments in a nicely formatted table.
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
 
 ```dvc
 $ dvc exp show
@@ -231,14 +228,15 @@ $ dvc exp show
 
 ![](/img/start-dvc-exp-show-210704.png)
 
-By default it shows all the parameters and the metrics along with the timestamp.
-If you have large number of parameters, metrics or experiments, this may lead to
-a cluttered view. You can limit the table to specific metrics, or parameters, or
+By default it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
 ```dvc
-$ dvc exp show --no-timestamp --include-params model.conv_units --include-metrics acc
+$ dvc exp show --no-timestamp \
+  --include-params model.conv_units --include-metrics acc
 ```
 
 ![](/img/start-dvc-exp-show-no-timestamp-210704.png)
@@ -278,7 +276,7 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## A note on experiment names
+## Note on experiment names
 
 When you create an experiment, DVC generates a hash value from the contents of
 the experiment. This is shown when you use `--queue` option, e.g.,
@@ -289,9 +287,9 @@ Queued experiment '6518f17' for future execution.
 ```
 
 After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-` by default, and can be set via
+the experiment. Typically these start with `exp-`, and can be set via
 `--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value:
+the name, you can see the hash value as _queued experiment_:
 
 ```dvc
 $ dvc exp run --queue --name cnn-512 -S model.conv_units=512

From fcf8aea2208ecd2a62623d93d913553cd22df340 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 6 Jul 2021 19:19:33 +0300
Subject: [PATCH 55/89] carried over changes in draft-1 and updated the install
 instructions

---
 .../start/experiments-trail/experiments-2.md  | 171 ++++++++++++------
 1 file changed, 119 insertions(+), 52 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 2fdc1e50b0..5a6c0dd5fc 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -12,19 +12,19 @@ your repo doesn't become polluted with all of them. You can discard experiments
 once they're no longer needed.
 
 Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). Let's further
-increase the number of features in the `featurize` stage to see how it compares.
+[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
+will explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
-In this section, we will explore the basic features of DVC experiment management
-with `[get-started-experiments]` project.
+[gse]: https://github.com/iterative/get-started-experiments
 
-get-started-experiments: https://github.com/iterative/get-started-experiments
+<details>
 
-## Installing and Configuring the Project
+## Installing the Project
 
-These commands are run in the `[get-started-experiments]` project. You can run
-the commands in this document after cloning the repository and installing the
-requirements.
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
 
 ### Clone the project and create virtual environment
 
@@ -43,10 +43,9 @@ $ python -m pip install -r requirements.txt
 
 ### Get the data set
 
-The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from the `dataset-registry`, we use `dvc pull` to update
-the missing data files. `dvc pull` is used in DVC repositories to update the
-missing data dependencies.
+The repository we cloned doesn't contain the dataset. In order to get the
+dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
+in DVC repositories to update the missing data dependencies.
 
 ```dvc
 $ dvc pull
@@ -64,14 +63,15 @@ experiments, please refer to the last section.
 
 </details>
 
-## Running the experiments with default parameters
+## Running the experiment with default parameters
 
-The purpose of `dvc exp` commands is to run the pipeline for ephemeral
+The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the experiments with default values requires only the command:
+Running the experiment with default hyperparameter values requires only the
+command:
 
 ```dvc
 $ dvc exp run
@@ -92,7 +92,7 @@ It runs the pipeline starting from the basic dependencies and produces
 ### If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may be used to `dvc repro`.
+have a DVC project, you may already be using `dvc repro`.
 
 In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
 pipeline.
@@ -100,16 +100,16 @@ pipeline.
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
 All the parameters and dependencies are retrieved from the current workspace. It
 doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit into Git, it's better to use
-`dvc exp run`. It allows to change the parameters quickly, can track the history
-of artifacts and has facilities to compare these experiments easily.
+number of experiments that you don't want to commit all to Git, it's better to
+use `dvc exp run`. It allows to change the parameters quickly, can track the
+history of artifacts and has facilities to compare these experiments easily.
 
-`dvc repro` is still available to run the pipeline that don't need these extra
-features.
+`dvc repro` is still available to run the pipeline when these extra features are
+not needed.
 
 </details>
 
-## Running the experiments by setting parameters
+## Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -118,7 +118,7 @@ the files manually. We use this feature to set the convolutional units in
 `train.py`.
 
 ```dvc
-$ dvc exp run --set-param conv_units=24
+$ dvc exp run --set-param model.conv_units=24
 ...
 Reproduced experiment(s): exp-6c06d
 Experiment results have been applied to your workspace.
@@ -142,11 +142,10 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
-### Run multiple experiments in parallel
+## Run multiple experiments in parallel
 
-Instead of running the experiments one-by-one, we can define them first to run
-them in a batch. This is especially handy when you have long running
-experiments.
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
 
 We add experiments to the queue using the `--queue` option of `dvc exp run`. We
 also use `-S` (`--set-param`) to set a value for the parameter.
@@ -166,32 +165,35 @@ Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
-TK
 ```
 
+It runs all the experiments, with the specified number of processes in parallel.
+
 ## Comparing experiments
 
-The pipeline is run several times with different parameters. To compare all of
-these experiments, we use `dvc exp show`. This command presents the parameters
-and metrics produced in experiments in a nicely formatted table.
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
 
 ```dvc
 $ dvc exp show
 ```
 
-TK
+![](/img/start-dvc-exp-show-210704.png)
 
-By default it shows all the parameters and the metrics along with the timestamp.
-If you have large number of parameters, metrics or experiments, this may lead to
-a cluttered view. You can limit the table to specific metrics, or parameters, or
+By default it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
 ```dvc
-$ dvc exp show --no-timestamp --include-params conv_units --include-metrics acc
-TK
+$ dvc exp show --no-timestamp \
+  --include-params model.conv_units --include-metrics acc
 ```
 
+![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+
 ## Persisting experiments
 
 After selecting a experiments from the table, you can commit the hyperparameters
@@ -202,8 +204,8 @@ history.
 experiment to the <abbr>workspace</abbr>.
 
 ```dvc
-$ dvc exp apply
-TK
+$ dvc exp apply exp-cb13f
+Changes for experiment 'exp-cb13f' have been applied to your current workspace.
 ```
 
 We can see the changes in the repository and commit them to Git.
@@ -214,14 +216,74 @@ $ git add .
 $ git commit -m "Successful experiment"
 ```
 
-### Preparing an experiments pipeline
+It may also be desirable to commit a particular experiment to a Git branch
+directly, without bringing to the workspace.
+
+```dvc
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
+
+        git checkout cnn-256
+```
+
+You can then checkout and continue from working this branch as usual.
+
+## Note on experiment names
+
+When you create an experiment, DVC generates a hash value from the contents of
+the experiment. This is shown when you use `--queue` option, e.g.,
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+```
+
+After _running_ the experiment, DVC uses another auto-generated name to refer to
+the experiment. Typically these start with `exp-`, and can be set via
+`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
+the name, you can see the hash value as _queued experiment_:
+
+```dvc
+$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
+Queued experiment '86bd8f9' for future execution.
+```
+
+In `dvc exp show` you can see both of these names:
+
+```dvc
+$ dvc exp show --no-pager --no-timestamp \
+      --include-metrics loss --include-params model.conv_units
+
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ Experiment              ┃ loss    ┃ model.conv_units ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.23534 │ 64               │
+│ 3973b6b                 │ -       │ 16               │
+│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
+│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
+│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
+│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
+│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
+│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
+│ └── *86bd8f9            │ -       │ 512              │
+└─────────────────────────┴─────────┴──────────────────┘
+```
+
+When an experiment is not run yet, only the former hash value is shown.
+
+You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
+running the experiment with the name starting with `exp-`, or the name you have
+supplied with `dvc exp run --name`.
+
+## Preparing a project for DVC experiments
 
 At the beginning of this document, we assumed that there is already a configured
 DVC project to simplify the introduction. DVC experiments are a feature added in
-DVC 2.0 and requires a DVC pipeline is defined in the project. In this section
-we'll show how to configure a project to run DVC experiments. You can get
-detailed information about these commands in other sections of DVC
-documentation.
+DVC 2.0 and requires a DVC pipeline defined in the project. In this section
+we'll show how to configure a project to run DVC experiments.
+
+Please refer to [install](/doc/install) if DVC is not installed in your system.
 
 If DVC is not initialized before in the project, you can do so by:
 
@@ -233,20 +295,25 @@ DVC also requires commands to be run and their dependencies to be defined as
 stages. We use `dvc stage add` to add a stage and set its dependencies.
 
 ```dvc
-$ dvc stage add
-TK
+$ dvc stage add -n train \
+                -p model.conv_units \
+                -p train.epochs \
+                -d data/images \
+                -m metrics.json \
+                python3 src/train.py
 ```
 
+The command tells DVC to create an experiment named `train`, and that for any
+change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
+experiment using `src/train.py` that produces a new `metrics.json` file.
+
 Note that the parameters (added with `-p`) are in the default parameters file
 `params.yaml` and used in the code as normal, by reading the file. DVC only
 tracks the changes and updates them with `--set-param`.
 
-## Go Further
+DVC is ready to run the experiments now!
 
-You can continue to experiment with
-[the project](https://github.com/iterative/get-started-experiments). Please see
-the `README.md` file of the project for these. Don't forget to
-[notify us](https://dvc.org/chat) if you happen to find good parameters.
+## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From b0d48d37c3b4937de2cea4d6a55f089285b98106 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 8 Jul 2021 12:50:19 +0300
Subject: [PATCH 56/89] merged and simplified the first paragraph and added
 emojis

---
 .../start/experiments-trail/experiments-1.md  | 38 ++++++++-----------
 1 file changed, 16 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index c0d2dde4dd..34c12c77bf 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -4,29 +4,23 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
-will explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
+<abbr>Experiments</abbr> grow in numbers where there are many parameters to
+tune. We can organize such experiments and keep only what we ultimately need
+with `dvc experiments`. DVC can track experiments for you so there's no need to
+commit each one to Git. We explore the basic features of DVC experiment
+management with [`get-started-experiments`][gse] project in this section.
 
 [gse]: https://github.com/iterative/get-started-experiments
 
 <details>
 
-### Installing and Configuring the Project
+### ⚙️ Installing and Configuring the Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### Clone the project and create virtual environment
+### 👥 Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -41,7 +35,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### Get the data set
+### 📀 Get the data set
 
 The repository you cloned doesn't contain the dataset. In order to get
 `fashion-mnist.tar.gz` from `dataset-registry`, we use `dvc get` to download the
@@ -59,7 +53,7 @@ Then we extract this file that contains labeled images.
 $ tar -xvzf data/images.tar.gz --directory data/
 ```
 
-### Specify the experiment
+### 🏹 Specify the experiment
 
 We first initialize DVC inside the project to create an experiment.
 
@@ -110,7 +104,7 @@ DVC is ready to run the experiments now!
 
 </details>
 
-## Running the experiment with default parameters
+## 👟 Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
@@ -136,7 +130,7 @@ It runs the pipeline starting from the basic dependencies and produces
 
 <details>
 
-### If you used `dvc repro` before
+### 📜 If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -156,7 +150,7 @@ not needed.
 
 </details>
 
-## Running the experiment by setting parameters
+## 🧥 Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -189,7 +183,7 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
-## Run multiple experiments in parallel
+## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -241,7 +235,7 @@ $ dvc exp show --no-timestamp \
 
 ![](/img/start-dvc-exp-show-no-timestamp-210704.png)
 
-## Persisting experiments
+## 🔏 Persisting experiments
 
 After selecting a experiments from the table, you can commit the hyperparameters
 and other dependencies that produced this successful experiment to your Git
@@ -276,7 +270,7 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## Note on experiment names
+## 📛 Note on experiment names
 
 When you create an experiment, DVC generates a hash value from the contents of
 the experiment. This is shown when you use `--queue` option, e.g.,
@@ -323,7 +317,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## Go Further
+## 🪐 Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From fbf8c5e8121bf3eae9ca44ee5db336083b8f2617 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 8 Jul 2021 12:53:55 +0300
Subject: [PATCH 57/89] added links to the sidebar (tentative)

---
 content/docs/sidebar.json | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index 676f943a01..3557a10a18 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -34,6 +34,14 @@
       "katacoda": "https://katacoda.com/dvc/courses/get-started"
     },
     "children": [
+      {
+        "slug": "experiments-trail/experiments-1",
+        "label": "Experiments Trail (Alternative 1)"
+      },
+      {
+        "slug": "experiments-trail/experiments-2",
+        "label": "Experiments Trail (Alternative 2)"
+      },
       {
         "slug": "data-and-model-versioning",
         "tutorials": {

From f12d1b8f199cee540dbf8345821f9fc5fc8be6cd Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 9 Jul 2021 13:15:15 +0300
Subject: [PATCH 58/89] changes after jorge's review

---
 .../start/experiments-trail/experiments-1.md   | 18 ++++++------------
 1 file changed, 6 insertions(+), 12 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 34c12c77bf..12cd0b6589 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -111,22 +111,17 @@ experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the experiment with default hyperparameter values requires only the
-command:
+Running the experiment with default project settings requires only the command:
 
 ```dvc
 $ dvc exp run
 ...
 Reproduced experiment(s): exp-7683f
 Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
+...
 ```
 
-It runs the pipeline starting from the basic dependencies and produces
-`metrics.json` file for the default state.
+It runs the specified command that writes the metrics values to `metrics.json`.
 
 <details>
 
@@ -202,14 +197,13 @@ $ dvc exp run --queue -S model.conv_units=256
 Queued experiment '8bb6049' for future execution.
 ```
 
-Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
 ```
 
-It runs all the experiments, with the specified number of processes in parallel.
-
 ## Comparing experiments
 
 The experiments are run several times with different parameters. We use
@@ -237,7 +231,7 @@ $ dvc exp show --no-timestamp \
 
 ## 🔏 Persisting experiments
 
-After selecting a experiments from the table, you can commit the hyperparameters
+After selecting an experiment from the table, you can commit the hyperparameters
 and other dependencies that produced this successful experiment to your Git
 history.
 

From 91ee97bdbb1eecc499a5a87ac87576495d8bc341 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Mon, 12 Jul 2021 13:09:06 +0300
Subject: [PATCH 59/89] carried over changes in alt-1 to alt-2

---
 .../start/experiments-trail/experiments-2.md  | 38 ++++++++-----------
 1 file changed, 16 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 5a6c0dd5fc..43bd2af1cc 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -20,13 +20,13 @@ will explore the basic features of DVC experiment management with
 
 <details>
 
-## Installing the Project
+## ⚙️ Installing the Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### Clone the project and create virtual environment
+### 👥 Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -41,7 +41,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### Get the data set
+### 📀 Get the data set
 
 The repository we cloned doesn't contain the dataset. In order to get the
 dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
@@ -63,33 +63,28 @@ experiments, please refer to the last section.
 
 </details>
 
-## Running the experiment with default parameters
+## 👟 Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
 experiments. By _ephemeral_ we mean the experiments can be run without
 committing parameter and dependency changes to Git. Instead the artifacts
 produced for each experiment are tracked by DVC and persisted on demand.
 
-Running the experiment with default hyperparameter values requires only the
-command:
+Running the experiment with default project settings requires only the command:
 
 ```dvc
 $ dvc exp run
 ...
 Reproduced experiment(s): exp-7683f
 Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
+...
 ```
 
-It runs the pipeline starting from the basic dependencies and produces
-`metrics.json` file for the default state.
+It runs the specified command that writes the metrics values to `metrics.json`.
 
 <details>
 
-### If you used `dvc repro` before
+### 📜 If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -109,7 +104,7 @@ not needed.
 
 </details>
 
-## Running the experiment by setting parameters
+## 🧥 Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -142,7 +137,7 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
-## Run multiple experiments in parallel
+## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -161,14 +156,13 @@ $ dvc exp run --queue -S model.conv_units=256
 Queued experiment '8bb6049' for future execution.
 ```
 
-Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
 
 ```dvc
 $ dvc exp run --run-all --jobs 2
 ```
 
-It runs all the experiments, with the specified number of processes in parallel.
-
 ## Comparing experiments
 
 The experiments are run several times with different parameters. We use
@@ -194,9 +188,9 @@ $ dvc exp show --no-timestamp \
 
 ![](/img/start-dvc-exp-show-no-timestamp-210704.png)
 
-## Persisting experiments
+## 🔏 Persisting experiments
 
-After selecting a experiments from the table, you can commit the hyperparameters
+After selecting an experiment from the table, you can commit the hyperparameters
 and other dependencies that produced this successful experiment to your Git
 history.
 
@@ -229,7 +223,7 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## Note on experiment names
+## 📛 Note on experiment names
 
 When you create an experiment, DVC generates a hash value from the contents of
 the experiment. This is shown when you use `--queue` option, e.g.,
@@ -276,7 +270,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## Preparing a project for DVC experiments
+## ⏲ Preparing a project for DVC experiments
 
 At the beginning of this document, we assumed that there is already a configured
 DVC project to simplify the introduction. DVC experiments are a feature added in

From b7ad284872bf27301802fb063806eac6a92d798b Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Mon, 12 Jul 2021 13:18:26 +0300
Subject: [PATCH 60/89] added 3rd alternative to experiments trail

---
 content/docs/sidebar.json                     |   4 +
 .../start/experiments-trail/experiments-3.md  | 319 ++++++++++++++++++
 2 files changed, 323 insertions(+)
 create mode 100644 content/docs/start/experiments-trail/experiments-3.md

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index 3557a10a18..996b658bcf 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -42,6 +42,10 @@
         "slug": "experiments-trail/experiments-2",
         "label": "Experiments Trail (Alternative 2)"
       },
+      {
+        "slug": "experiments-trail/experiments-3",
+        "label": "Experiments Trail (Alternative 3)"
+      },
       {
         "slug": "data-and-model-versioning",
         "tutorials": {
diff --git a/content/docs/start/experiments-trail/experiments-3.md b/content/docs/start/experiments-trail/experiments-3.md
new file mode 100644
index 0000000000..b86b7db544
--- /dev/null
+++ b/content/docs/start/experiments-trail/experiments-3.md
@@ -0,0 +1,319 @@
+---
+title: 'Get Started: Experiments'
+---
+
+# Get Started with Experiments
+
+<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
+parameters to tune or other permutations of the code. We can organize such
+projects and keep only what we ultimately need with `dvc experiments`. DVC can
+track experiments for you so there's no need to commit each one to Git. This way
+your repo doesn't become polluted with all of them. You can discard experiments
+once they're no longer needed.
+
+Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
+[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
+will explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
+
+[gse]: https://github.com/iterative/get-started-experiments
+
+## ⚙️ Installing the Example Project
+
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
+
+### 👥 Clone the project and create virtual environment
+
+Please clone the project and create a virtual environment.
+
+> We create a virtual environment to keep the libraries we use isolated from the
+> rest of your system. This prevents version conflicts.
+
+```dvc
+$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
+```
+
+### 📀 Get the data set
+
+The repository we cloned doesn't contain the dataset. In order to get the
+dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
+in DVC repositories to update the missing data dependencies.
+
+```dvc
+$ dvc pull
+```
+
+Then we extract this file that contains labeled images.
+
+```dvc
+$ tar -xvzf data/images.tar.gz --directory data/
+```
+
+The repository already contains the necessary configuration to run the
+experiments. If you would like to learn how to configure a project to run DVC
+experiments, please refer to the last section.
+
+<details>
+
+## ⏲ Preparing a project for DVC experiments
+
+In this document we assume that there is already a configured DVC project to
+simplify the introduction. DVC experiments are a feature added in DVC 2.0 and
+requires a DVC pipeline defined in the project.
+
+Please refer to [install](/doc/install) if DVC is not installed in your system.
+
+If DVC is not initialized before in the project, you can do so by:
+
+```dvc
+$ dvc init
+```
+
+DVC also requires commands to be run and their dependencies to be defined as
+stages. We use `dvc stage add` to add a stage and set its dependencies.
+
+```dvc
+$ dvc stage add -n train \
+                -p model.conv_units \
+                -p train.epochs \
+                -d data/images \
+                -m metrics.json \
+                python3 src/train.py
+```
+
+The command tells DVC to create an experiment named `train`, and that for any
+change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
+experiment using `src/train.py` that produces a new `metrics.json` file.
+
+Note that the parameters (added with `-p`) are in the default parameters file
+`params.yaml` and used in the code as normal, by reading the file. DVC only
+tracks the changes and updates them with `--set-param`. For other files that
+contain the parameters, DVC expects the filename to be provided similar to
+`-p myparams.yaml:epochs`.
+
+DVC is ready to run the experiments now!
+
+</details>
+
+## 👟 Running the experiment with default parameters
+
+The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
+experiments. By _ephemeral_ we mean the experiments can be run without
+committing parameter and dependency changes to Git. Instead the artifacts
+produced for each experiment are tracked by DVC and persisted on demand.
+
+Running the experiment with default project settings requires only the command:
+
+```dvc
+$ dvc exp run
+...
+Reproduced experiment(s): exp-7683f
+Experiment results have been applied to your workspace.
+...
+```
+
+It runs the specified command that writes the metrics values to `metrics.json`.
+
+<details>
+
+### 📜 If you used `dvc repro` before
+
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may already be using `dvc repro`.
+
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
+pipeline.
+
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments. When you have large
+number of experiments that you don't want to commit all to Git, it's better to
+use `dvc exp run`. It allows to change the parameters quickly, can track the
+history of artifacts and has facilities to compare these experiments easily.
+
+`dvc repro` is still available to run the pipeline when these extra features are
+not needed.
+
+</details>
+
+## 🧥 Running the experiment by setting parameters
+
+Now let's do some more experimentation.
+
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
+
+```dvc
+$ dvc exp run --set-param model.conv_units=24
+...
+Reproduced experiment(s): exp-6c06d
+Experiment results have been applied to your workspace.
+
+To promote an experiment to a Git branch run:
+
+        dvc exp branch <exp>
+```
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
+can see the effect of it by looking at the diff.
+
+```dvc
+$ git diff params.yaml
+```
+
+```git
+-model:
+-  conv_units: 16
++model:
++  conv_units: 24
+```
+
+## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
+
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
+
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter.
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '30eb9b2' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment 'ac66940' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '8bb6049' for future execution.
+```
+
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
+
+```dvc
+$ dvc exp run --run-all --jobs 2
+```
+
+## Comparing experiments
+
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
+
+```dvc
+$ dvc exp show
+```
+
+![](/img/start-dvc-exp-show-210704.png)
+
+By default it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
+
+```dvc
+$ dvc exp show --no-timestamp \
+  --include-params model.conv_units --include-metrics acc
+```
+
+![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+
+## 🔏 Persisting experiments
+
+After selecting an experiment from the table, you can commit the hyperparameters
+and other dependencies that produced this successful experiment to your Git
+history.
+
+`dvc exp apply` brings back all specific artifacts and parameters from the
+experiment to the <abbr>workspace</abbr>.
+
+```dvc
+$ dvc exp apply exp-cb13f
+Changes for experiment 'exp-cb13f' have been applied to your current workspace.
+```
+
+We can see the changes in the repository and commit them to Git.
+
+```dvc
+$ git diff
+$ git add .
+$ git commit -m "Successful experiment"
+```
+
+It may also be desirable to commit a particular experiment to a Git branch
+directly, without bringing to the workspace.
+
+```dvc
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
+
+        git checkout cnn-256
+```
+
+You can then checkout and continue from working this branch as usual.
+
+## 📛 Note on experiment names
+
+When you create an experiment, DVC generates a hash value from the contents of
+the experiment. This is shown when you use `--queue` option, e.g.,
+
+```dvc
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '6518f17' for future execution.
+```
+
+After _running_ the experiment, DVC uses another auto-generated name to refer to
+the experiment. Typically these start with `exp-`, and can be set via
+`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
+the name, you can see the hash value as _queued experiment_:
+
+```dvc
+$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
+Queued experiment '86bd8f9' for future execution.
+```
+
+In `dvc exp show` you can see both of these names:
+
+```dvc
+$ dvc exp show --no-pager --no-timestamp \
+      --include-metrics loss --include-params model.conv_units
+
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ Experiment              ┃ loss    ┃ model.conv_units ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.23534 │ 64               │
+│ 3973b6b                 │ -       │ 16               │
+│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
+│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
+│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
+│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
+│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
+│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
+│ └── *86bd8f9            │ -       │ 512              │
+└─────────────────────────┴─────────┴──────────────────┘
+```
+
+When an experiment is not run yet, only the former hash value is shown.
+
+You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
+running the experiment with the name starting with `exp-`, or the name you have
+supplied with `dvc exp run --name`.
+
+## Go Further
+
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
+
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From 0b9772820576792696b7fb4d0c595702c7e96f8d Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Mon, 12 Jul 2021 13:47:12 +0300
Subject: [PATCH 61/89] minor changes

---
 content/docs/start/experiments-trail/experiments-1.md | 2 +-
 content/docs/start/experiments-trail/experiments-2.md | 4 ++--
 content/docs/start/experiments-trail/experiments-3.md | 4 ++--
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
index 12cd0b6589..44a334a33d 100644
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ b/content/docs/start/experiments-trail/experiments-1.md
@@ -204,7 +204,7 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
-## Comparing experiments
+## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
index 43bd2af1cc..fb63cdb049 100644
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ b/content/docs/start/experiments-trail/experiments-2.md
@@ -163,7 +163,7 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
-## Comparing experiments
+## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -307,7 +307,7 @@ tracks the changes and updates them with `--set-param`.
 
 DVC is ready to run the experiments now!
 
-## Go Further
+## 🪐 Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences
diff --git a/content/docs/start/experiments-trail/experiments-3.md b/content/docs/start/experiments-trail/experiments-3.md
index b86b7db544..46bbfcf116 100644
--- a/content/docs/start/experiments-trail/experiments-3.md
+++ b/content/docs/start/experiments-trail/experiments-3.md
@@ -201,7 +201,7 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
-## Comparing experiments
+## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -308,7 +308,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## Go Further
+## 🪐 Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From 5a925e9324ebb30c107085cfe228e751d62ad2f9 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 16 Jul 2021 19:53:13 +0300
Subject: [PATCH 62/89] removed alt-1 and alt-2

---
 .../start/experiments-trail/experiments-1.md  | 322 ------------------
 .../start/experiments-trail/experiments-2.md  | 318 -----------------
 2 files changed, 640 deletions(-)
 delete mode 100644 content/docs/start/experiments-trail/experiments-1.md
 delete mode 100644 content/docs/start/experiments-trail/experiments-2.md

diff --git a/content/docs/start/experiments-trail/experiments-1.md b/content/docs/start/experiments-trail/experiments-1.md
deleted file mode 100644
index 44a334a33d..0000000000
--- a/content/docs/start/experiments-trail/experiments-1.md
+++ /dev/null
@@ -1,322 +0,0 @@
----
-title: 'Get Started: Experiments'
----
-
-# Get Started with Experiments
-
-<abbr>Experiments</abbr> grow in numbers where there are many parameters to
-tune. We can organize such experiments and keep only what we ultimately need
-with `dvc experiments`. DVC can track experiments for you so there's no need to
-commit each one to Git. We explore the basic features of DVC experiment
-management with [`get-started-experiments`][gse] project in this section.
-
-[gse]: https://github.com/iterative/get-started-experiments
-
-<details>
-
-### ⚙️ Installing and Configuring the Project
-
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
-
-### 👥 Clone the project and create virtual environment
-
-Please clone the project and create a virtual environment.
-
-> We create a virtual environment to keep the libraries we use isolated from the
-> rest of your system. This prevents version conflicts.
-
-```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b source-code
-$ cd get-started-experiments
-$ virtualenv .venv
-$ . .venv/bin/activate
-$ python -m pip install -r requirements.txt
-```
-
-### 📀 Get the data set
-
-The repository you cloned doesn't contain the dataset. In order to get
-`fashion-mnist.tar.gz` from `dataset-registry`, we use `dvc get` to download the
-missing data files. `dvc get` is similar to `wget` but works with Git+DVC
-repositories to download binary files.
-
-```dvc
-$ dvc get https://github.com/iterative/dataset-registry \
-          fashion-mnist/images.tar.gz -o data/images.tar.gz
-```
-
-Then we extract this file that contains labeled images.
-
-```dvc
-$ tar -xvzf data/images.tar.gz --directory data/
-```
-
-### 🏹 Specify the experiment
-
-We first initialize DVC inside the project to create an experiment.
-
-```dvc
-$ dvc init
-```
-
-Then we add the dataset to the project:
-
-```dvc
-$ dvc add data/images
-```
-
-This creates a `data/images.dvc` file that contains all the relevant metadata of
-the directory. You can add and commit `data/images.dvc` file, and changes in
-`.gitignore` that hides the `data/images/` directory from Git.
-
-```dvc
-$ git add data/.gitignore data/images.dvc
-$ git commit -m "Dataset added"
-```
-
-DVC experiments are run by specifying their commands, outputs, parameters and
-dependencies. We specify an experiment command by `dvc stage add`.
-
-```dvc
-$ dvc stage add -n train \
-                -p model.conv_units \
-                -p train.epochs \
-                -d data/images \
-                -m metrics.json \
-                python3 src/train.py
-```
-
-The command tells DVC to create an experiment named `train`, and that for any
-change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
-experiment using `src/train.py` that produces a new `metrics.json` file.
-
-DVC creates `dvc.yaml` file and modifies `.gitignore` for Git to ignore certain
-artifacts.
-
-```dvc
-$ git add dvc.yaml .gitignore
-$ git commit -m "added data and the experiment"
-```
-
-DVC is ready to run the experiments now!
-
-</details>
-
-## 👟 Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
-experiments. By _ephemeral_ we mean the experiments can be run without
-committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment are tracked by DVC and persisted on demand.
-
-Running the experiment with default project settings requires only the command:
-
-```dvc
-$ dvc exp run
-...
-Reproduced experiment(s): exp-7683f
-Experiment results have been applied to your workspace.
-...
-```
-
-It runs the specified command that writes the metrics values to `metrics.json`.
-
-<details>
-
-### 📜 If you used `dvc repro` before
-
-Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may already be using `dvc repro`.
-
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
-pipeline.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit all to Git, it's better to
-use `dvc exp run`. It allows to change the parameters quickly, can track the
-history of artifacts and has facilities to compare these experiments easily.
-
-`dvc repro` is still available to run the pipeline when these extra features are
-not needed.
-
-</details>
-
-## 🧥 Running the experiment by setting parameters
-
-Now let's do some more experimentation.
-
-DVC allows to update the parameters defined in the pipeline without modifying
-the files manually. We use this feature to set the convolutional units in
-`train.py`.
-
-```dvc
-$ dvc exp run --set-param model.conv_units=24
-...
-Reproduced experiment(s): exp-6c06d
-Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
-```
-
-When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
-can see the effect of it by looking at the diff.
-
-```dvc
-$ git diff params.yaml
-```
-
-```git
--model:
--  conv_units: 16
-+model:
-+  conv_units: 24
-```
-
-## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
-
-Instead of running the experiments one-by-one, we can define them to run in a
-batch. This is especially handy when you have long running experiments.
-
-We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter.
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-$ dvc exp run --queue -S model.conv_units=64
-Queued experiment '30eb9b2' for future execution.
-$ dvc exp run --queue -S model.conv_units=128
-Queued experiment 'ac66940' for future execution.
-$ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.
-```
-
-Next, run all (`--run-all`) queued experiments in parallel. You can specify the
-number of parallel processes using `--jobs`:
-
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
-
-## ↔️ Comparing experiments
-
-The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
-
-```dvc
-$ dvc exp show
-```
-
-![](/img/start-dvc-exp-show-210704.png)
-
-By default it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
-hide the timestamp column with `--include-metrics`, `--include-params`, or
-`--no-timestamp` options of the command, respectively.
-
-```dvc
-$ dvc exp show --no-timestamp \
-  --include-params model.conv_units --include-metrics acc
-```
-
-![](/img/start-dvc-exp-show-no-timestamp-210704.png)
-
-## 🔏 Persisting experiments
-
-After selecting an experiment from the table, you can commit the hyperparameters
-and other dependencies that produced this successful experiment to your Git
-history.
-
-`dvc exp apply` brings back all specific artifacts and parameters from the
-experiment to the <abbr>workspace</abbr>.
-
-```dvc
-$ dvc exp apply exp-cb13f
-Changes for experiment 'exp-cb13f' have been applied to your current workspace.
-```
-
-We can see the changes in the repository and commit them to Git.
-
-```dvc
-$ git diff
-$ git add .
-$ git commit -m "Successful experiment"
-```
-
-It may also be desirable to commit a particular experiment to a Git branch
-directly, without bringing to the workspace.
-
-```dvc
-$ dvc exp branch exp-05e87 "cnn-256"
-Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
-To switch to the new branch run:
-
-        git checkout cnn-256
-```
-
-You can then checkout and continue from working this branch as usual.
-
-## 📛 Note on experiment names
-
-When you create an experiment, DVC generates a hash value from the contents of
-the experiment. This is shown when you use `--queue` option, e.g.,
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-```
-
-After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-`, and can be set via
-`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value as _queued experiment_:
-
-```dvc
-$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
-Queued experiment '86bd8f9' for future execution.
-```
-
-In `dvc exp show` you can see both of these names:
-
-```dvc
-$ dvc exp show --no-pager --no-timestamp \
-      --include-metrics loss --include-params model.conv_units
-
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ Experiment              ┃ loss    ┃ model.conv_units ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.23534 │ 64               │
-│ 3973b6b                 │ -       │ 16               │
-│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
-│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
-│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
-│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
-│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
-│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
-│ └── *86bd8f9            │ -       │ 512              │
-└─────────────────────────┴─────────┴──────────────────┘
-```
-
-When an experiment is not run yet, only the former hash value is shown.
-
-You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
-running the experiment with the name starting with `exp-`, or the name you have
-supplied with `dvc exp run --name`.
-
-## 🪐 Go Further
-
-There are many other features of `dvc exp`, like cleaning up the unused
-experiments, sharing them without committing into Git or getting differences
-between two experiments.
-
-Please see the section on
-[Experiment Management](/doc/user-guide/experiment-management) in the User's
-Guide or `dvc exp` and subcommands in the Command Reference.
diff --git a/content/docs/start/experiments-trail/experiments-2.md b/content/docs/start/experiments-trail/experiments-2.md
deleted file mode 100644
index fb63cdb049..0000000000
--- a/content/docs/start/experiments-trail/experiments-2.md
+++ /dev/null
@@ -1,318 +0,0 @@
----
-title: 'Get Started: Experiments'
----
-
-# Get Started with Experiments
-
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
-will explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
-
-[gse]: https://github.com/iterative/get-started-experiments
-
-<details>
-
-## ⚙️ Installing the Project
-
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
-
-### 👥 Clone the project and create virtual environment
-
-Please clone the project and create a virtual environment.
-
-> We create a virtual environment to keep the libraries we use isolated from the
-> rest of your system. This prevents version conflicts.
-
-```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
-$ cd get-started-experiments
-$ virtualenv .venv
-$ . .venv/bin/activate
-$ python -m pip install -r requirements.txt
-```
-
-### 📀 Get the data set
-
-The repository we cloned doesn't contain the dataset. In order to get the
-dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
-in DVC repositories to update the missing data dependencies.
-
-```dvc
-$ dvc pull
-```
-
-Then we extract this file that contains labeled images.
-
-```dvc
-$ tar -xvzf data/images.tar.gz --directory data/
-```
-
-The repository already contains the necessary configuration to run the
-experiments. If you would like to learn how to configure a project to run DVC
-experiments, please refer to the last section.
-
-</details>
-
-## 👟 Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
-experiments. By _ephemeral_ we mean the experiments can be run without
-committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment are tracked by DVC and persisted on demand.
-
-Running the experiment with default project settings requires only the command:
-
-```dvc
-$ dvc exp run
-...
-Reproduced experiment(s): exp-7683f
-Experiment results have been applied to your workspace.
-...
-```
-
-It runs the specified command that writes the metrics values to `metrics.json`.
-
-<details>
-
-### 📜 If you used `dvc repro` before
-
-Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may already be using `dvc repro`.
-
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
-pipeline.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit all to Git, it's better to
-use `dvc exp run`. It allows to change the parameters quickly, can track the
-history of artifacts and has facilities to compare these experiments easily.
-
-`dvc repro` is still available to run the pipeline when these extra features are
-not needed.
-
-</details>
-
-## 🧥 Running the experiment by setting parameters
-
-Now let's do some more experimentation.
-
-DVC allows to update the parameters defined in the pipeline without modifying
-the files manually. We use this feature to set the convolutional units in
-`train.py`.
-
-```dvc
-$ dvc exp run --set-param model.conv_units=24
-...
-Reproduced experiment(s): exp-6c06d
-Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
-```
-
-When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
-can see the effect of it by looking at the diff.
-
-```dvc
-$ git diff params.yaml
-```
-
-```git
--model:
--  conv_units: 16
-+model:
-+  conv_units: 24
-```
-
-## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
-
-Instead of running the experiments one-by-one, we can define them to run in a
-batch. This is especially handy when you have long running experiments.
-
-We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter.
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-$ dvc exp run --queue -S model.conv_units=64
-Queued experiment '30eb9b2' for future execution.
-$ dvc exp run --queue -S model.conv_units=128
-Queued experiment 'ac66940' for future execution.
-$ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.
-```
-
-Next, run all (`--run-all`) queued experiments in parallel. You can specify the
-number of parallel processes using `--jobs`:
-
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
-
-## ↔️ Comparing experiments
-
-The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
-
-```dvc
-$ dvc exp show
-```
-
-![](/img/start-dvc-exp-show-210704.png)
-
-By default it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
-hide the timestamp column with `--include-metrics`, `--include-params`, or
-`--no-timestamp` options of the command, respectively.
-
-```dvc
-$ dvc exp show --no-timestamp \
-  --include-params model.conv_units --include-metrics acc
-```
-
-![](/img/start-dvc-exp-show-no-timestamp-210704.png)
-
-## 🔏 Persisting experiments
-
-After selecting an experiment from the table, you can commit the hyperparameters
-and other dependencies that produced this successful experiment to your Git
-history.
-
-`dvc exp apply` brings back all specific artifacts and parameters from the
-experiment to the <abbr>workspace</abbr>.
-
-```dvc
-$ dvc exp apply exp-cb13f
-Changes for experiment 'exp-cb13f' have been applied to your current workspace.
-```
-
-We can see the changes in the repository and commit them to Git.
-
-```dvc
-$ git diff
-$ git add .
-$ git commit -m "Successful experiment"
-```
-
-It may also be desirable to commit a particular experiment to a Git branch
-directly, without bringing to the workspace.
-
-```dvc
-$ dvc exp branch exp-05e87 "cnn-256"
-Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
-To switch to the new branch run:
-
-        git checkout cnn-256
-```
-
-You can then checkout and continue from working this branch as usual.
-
-## 📛 Note on experiment names
-
-When you create an experiment, DVC generates a hash value from the contents of
-the experiment. This is shown when you use `--queue` option, e.g.,
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-```
-
-After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-`, and can be set via
-`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value as _queued experiment_:
-
-```dvc
-$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
-Queued experiment '86bd8f9' for future execution.
-```
-
-In `dvc exp show` you can see both of these names:
-
-```dvc
-$ dvc exp show --no-pager --no-timestamp \
-      --include-metrics loss --include-params model.conv_units
-
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ Experiment              ┃ loss    ┃ model.conv_units ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.23534 │ 64               │
-│ 3973b6b                 │ -       │ 16               │
-│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
-│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
-│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
-│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
-│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
-│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
-│ └── *86bd8f9            │ -       │ 512              │
-└─────────────────────────┴─────────┴──────────────────┘
-```
-
-When an experiment is not run yet, only the former hash value is shown.
-
-You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
-running the experiment with the name starting with `exp-`, or the name you have
-supplied with `dvc exp run --name`.
-
-## ⏲ Preparing a project for DVC experiments
-
-At the beginning of this document, we assumed that there is already a configured
-DVC project to simplify the introduction. DVC experiments are a feature added in
-DVC 2.0 and requires a DVC pipeline defined in the project. In this section
-we'll show how to configure a project to run DVC experiments.
-
-Please refer to [install](/doc/install) if DVC is not installed in your system.
-
-If DVC is not initialized before in the project, you can do so by:
-
-```dvc
-$ dvc init
-```
-
-DVC also requires commands to be run and their dependencies to be defined as
-stages. We use `dvc stage add` to add a stage and set its dependencies.
-
-```dvc
-$ dvc stage add -n train \
-                -p model.conv_units \
-                -p train.epochs \
-                -d data/images \
-                -m metrics.json \
-                python3 src/train.py
-```
-
-The command tells DVC to create an experiment named `train`, and that for any
-change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
-experiment using `src/train.py` that produces a new `metrics.json` file.
-
-Note that the parameters (added with `-p`) are in the default parameters file
-`params.yaml` and used in the code as normal, by reading the file. DVC only
-tracks the changes and updates them with `--set-param`.
-
-DVC is ready to run the experiments now!
-
-## 🪐 Go Further
-
-There are many other features of `dvc exp`, like cleaning up the unused
-experiments, sharing them without committing into Git or getting differences
-between two experiments.
-
-Please see the section on
-[Experiment Management](/doc/user-guide/experiment-management) in the User's
-Guide or `dvc exp` and subcommands in the Command Reference.

From 3c6a9b2b2c7944f6fb16dc79cd8c09b2d8e85f8a Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 16 Jul 2021 19:56:07 +0300
Subject: [PATCH 63/89] renamed experiments trail alt-3 and modified the
 sidebar

---
 content/docs/sidebar.json                         | 15 ++-------------
 .../{experiments-3.md => experiments.md}          |  0
 2 files changed, 2 insertions(+), 13 deletions(-)
 rename content/docs/start/experiments-trail/{experiments-3.md => experiments.md} (100%)

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index 996b658bcf..c716a6319c 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -34,18 +34,6 @@
       "katacoda": "https://katacoda.com/dvc/courses/get-started"
     },
     "children": [
-      {
-        "slug": "experiments-trail/experiments-1",
-        "label": "Experiments Trail (Alternative 1)"
-      },
-      {
-        "slug": "experiments-trail/experiments-2",
-        "label": "Experiments Trail (Alternative 2)"
-      },
-      {
-        "slug": "experiments-trail/experiments-3",
-        "label": "Experiments Trail (Alternative 3)"
-      },
       {
         "slug": "data-and-model-versioning",
         "tutorials": {
@@ -72,7 +60,8 @@
         }
       },
       {
-        "slug": "experiments",
+        "slug": "experiments-trail/experiments",
+        "label": "Experiments Trail",
         "tutorials": {
           "katacoda": "https://katacoda.com/dvc/courses/get-started/experiments"
         }
diff --git a/content/docs/start/experiments-trail/experiments-3.md b/content/docs/start/experiments-trail/experiments.md
similarity index 100%
rename from content/docs/start/experiments-trail/experiments-3.md
rename to content/docs/start/experiments-trail/experiments.md

From 8433c8f9d5e19591d5e60b7433765b220c7d4201 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Tue, 20 Jul 2021 19:22:18 +0300
Subject: [PATCH 64/89] minor changes for experiment commands

---
 .../start/experiments-trail/experiments.md    | 19 ++++++++-----------
 1 file changed, 8 insertions(+), 11 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 46bbfcf116..a5505aa3f5 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -32,7 +32,7 @@ Please clone the project and create a virtual environment.
 > rest of your system. This prevents version conflicts.
 
 ```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b pipeline-added
+$ git clone https://github.com/iterative/get-started-experiments -b get-started
 $ cd get-started-experiments
 $ virtualenv .venv
 $ . .venv/bin/activate
@@ -113,7 +113,7 @@ Running the experiment with default project settings requires only the command:
 ```dvc
 $ dvc exp run
 ...
-Reproduced experiment(s): exp-7683f
+Reproduced experiment(s): exp-b28f0
 Experiment results have been applied to your workspace.
 ...
 ```
@@ -153,12 +153,9 @@ the files manually. We use this feature to set the convolutional units in
 ```dvc
 $ dvc exp run --set-param model.conv_units=24
 ...
-Reproduced experiment(s): exp-6c06d
+Reproduced experiment(s): exp-7b56f
 Experiment results have been applied to your workspace.
-
-To promote an experiment to a Git branch run:
-
-        dvc exp branch <exp>
+...
 ```
 
 When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
@@ -185,13 +182,13 @@ also use `-S` (`--set-param`) to set a value for the parameter.
 
 ```dvc
 $ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
+Queued experiment '3cac8c6' for future execution.
 $ dvc exp run --queue -S model.conv_units=64
-Queued experiment '30eb9b2' for future execution.
+Queued experiment '23660b6' for future execution.
 $ dvc exp run --queue -S model.conv_units=128
-Queued experiment 'ac66940' for future execution.
+Queued experiment '6591a57' for future execution.
 $ dvc exp run --queue -S model.conv_units=256
-Queued experiment '8bb6049' for future execution.
+Queued experiment '9109ea9' for future execution.
 ```
 
 Next, run all (`--run-all`) queued experiments in parallel. You can specify the

From f6b870b5cf22a78f56e7b10f21a83d50a890a394 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 22 Jul 2021 14:56:12 +0300
Subject: [PATCH 65/89] updated the experiments  and removed some text

---
 .../start/experiments-trail/experiments.md    | 65 ++++++++++++-------
 1 file changed, 43 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index a5505aa3f5..ab29543112 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -49,23 +49,16 @@ in DVC repositories to update the missing data dependencies.
 $ dvc pull
 ```
 
-Then we extract this file that contains labeled images.
-
-```dvc
-$ tar -xvzf data/images.tar.gz --directory data/
-```
-
 The repository already contains the necessary configuration to run the
-experiments. If you would like to learn how to configure a project to run DVC
-experiments, please refer to the last section.
+experiments.
 
 <details>
 
 ## ⏲ Preparing a project for DVC experiments
 
 In this document we assume that there is already a configured DVC project to
-simplify the introduction. DVC experiments are a feature added in DVC 2.0 and
-requires a DVC pipeline defined in the project.
+simplify the introduction. DVC experiments require a DVC pipeline defined in the
+project.
 
 Please refer to [install](/doc/install) if DVC is not installed in your system.
 
@@ -91,22 +84,20 @@ The command tells DVC to create an experiment named `train`, and that for any
 change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
 experiment using `src/train.py` that produces a new `metrics.json` file.
 
-Note that the parameters (added with `-p`) are in the default parameters file
-`params.yaml` and used in the code as normal, by reading the file. DVC only
-tracks the changes and updates them with `--set-param`. For other files that
-contain the parameters, DVC expects the filename to be provided similar to
-`-p myparams.yaml:epochs`.
+You can get more information on [pipelines], and [parameters] in other sections
+of this guide.
 
-DVC is ready to run the experiments now!
+[pipelines]: /doc/start/data-pipelines
+[parameters]: /doc/start/metrics-parameters-plots
 
 </details>
 
 ## 👟 Running the experiment with default parameters
 
-The purpose of `dvc exp` subcommands is to run the pipeline for ephemeral
-experiments. By _ephemeral_ we mean the experiments can be run without
-committing parameter and dependency changes to Git. Instead the artifacts
-produced for each experiment are tracked by DVC and persisted on demand.
+The purpose of `dvc exp` subcommands is to run the pipeline for experiments
+without committing parameter and dependency changes to Git. Instead the
+artifacts produced for each experiment are tracked by DVC and persisted on
+demand.
 
 Running the experiment with default project settings requires only the command:
 
@@ -172,6 +163,8 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
+<details>
+
 ## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
@@ -198,6 +191,8 @@ number of parallel processes using `--jobs`:
 $ dvc exp run --run-all --jobs 2
 ```
 
+</details>
+
 ## ↔️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
@@ -208,7 +203,20 @@ parameters and metrics produced in experiments in a nicely formatted table.
 $ dvc exp show
 ```
 
-![](/img/start-dvc-exp-show-210704.png)
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**    ┃ white:**Created**┃    yellow:**loss** ┃    yellow:**acc** ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 05:14 PM     │ 0.23146 │ 0.9145 │ 10           │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 05:14 PM     │ 0.25231 │ 0.9102 │ 10           │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 04:46 PM     │ 0.23687 │ 0.9167 │ 10           │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 04:46 PM     │ 0.24459 │ 0.9134 │ 10           │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 03:35 PM     │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
+└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
+```
 
 By default it shows all the parameters and the metrics with the timestamp. If
 you have large number of parameters, metrics or experiments, this may lead to a
@@ -221,7 +229,20 @@ $ dvc exp show --no-timestamp \
   --include-params model.conv_units --include-metrics acc
 ```
 
-![](/img/start-dvc-exp-show-no-timestamp-210704.png)
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃    yellow:**acc** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.9151 │ 24               │
+│ 7317bc6                 │      - │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 0.9145 │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 0.9102 │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 0.9167 │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 0.9134 │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 0.9151 │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 0.9152 │ 16               │
+└─────────────────────────┴────────┴──────────────────┘
+```
 
 ## 🔏 Persisting experiments
 

From b2050b9582797ce030ad6c2dd80f69a9077d6d76 Mon Sep 17 00:00:00 2001
From: "github@emresult.com" <github@emresult.com>
Date: Wed, 28 Jul 2021 14:35:30 +0000
Subject: [PATCH 66/89] Updated and simplified initial paragraphs

---
 .../docs/start/experiments-trail/experiments.md | 17 ++++++-----------
 1 file changed, 6 insertions(+), 11 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index ab29543112..9e17d22eb9 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -4,17 +4,12 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc experiments`. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). In this section, we
-will explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
+<abbr>Experiments</abbr> grow rapidly in number in ML projects. DVC can track
+these experiments, list their most relevant parameters and metrics, and commit
+only the ones that we need to Git.
+
+In this section, we will explore the basic features of DVC experiment management
+with [`get-started-experiments`][gse] project.
 
 [gse]: https://github.com/iterative/get-started-experiments
 

From 690b3912540d3542d0c6e4639e1fe2bd4194ac37 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Fri, 30 Jul 2021 14:21:47 +0300
Subject: [PATCH 67/89] updated the details section scope to hide all
 installation info

---
 content/docs/start/experiments-trail/experiments.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 9e17d22eb9..1d3bc71f09 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -13,6 +13,8 @@ with [`get-started-experiments`][gse] project.
 
 [gse]: https://github.com/iterative/get-started-experiments
 
+<details>
+
 ## ⚙️ Installing the Example Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
@@ -47,8 +49,6 @@ $ dvc pull
 The repository already contains the necessary configuration to run the
 experiments.
 
-<details>
-
 ## ⏲ Preparing a project for DVC experiments
 
 In this document we assume that there is already a configured DVC project to

From 4be613886b97dc9b2a4881015b2fe135e9ad2e04 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 30 Jul 2021 14:45:53 +0300
Subject: [PATCH 68/89] moved params diff explanation to hidden section + minor
 edits

---
 .../start/experiments-trail/experiments.md    | 19 +++++++++++++------
 1 file changed, 13 insertions(+), 6 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 1d3bc71f09..080ba99177 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -4,9 +4,9 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-<abbr>Experiments</abbr> grow rapidly in number in ML projects. DVC can track
-these experiments, list their most relevant parameters and metrics, and commit
-only the ones that we need to Git.
+In machine learning projects, number of <abbr>experiments</abbr> grow rapidly.
+DVC can track these experiments, list their most relevant parameters and
+metrics, and commit only the ones that we need to Git.
 
 In this section, we will explore the basic features of DVC experiment management
 with [`get-started-experiments`][gse] project.
@@ -144,8 +144,13 @@ Experiment results have been applied to your workspace.
 ...
 ```
 
-When you run `dvc exp run` with `--set-param`, it updates the parameter file. We
-can see the effect of it by looking at the diff.
+<details>
+
+### How DVC updates the parameters?
+
+When you run `dvc exp run` with `--set-param`, it updates the parameter file.
+(Default: `params.yaml`) We can see the effect of DVC updating the parameters by
+looking at the diff.
 
 ```dvc
 $ git diff params.yaml
@@ -158,9 +163,11 @@ $ git diff params.yaml
 +  conv_units: 24
 ```
 
+</details>
+
 <details>
 
-## 🏃‍♂️🏃🏾‍♂️🏃🏻‍♂️ Run multiple experiments in parallel
+## 👟👟 Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.

From c2e00f56275c80d48ba3baae03234853487abd50 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 10:52:17 +0300
Subject: [PATCH 69/89] replaced some emoji

---
 content/docs/start/experiments-trail/experiments.md | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 080ba99177..09999c083d 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -21,7 +21,7 @@ These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### 👥 Clone the project and create virtual environment
+### ⚡ Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -36,7 +36,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### 📀 Get the data set
+### ✅ Get the data set
 
 The repository we cloned doesn't contain the dataset. In order to get the
 dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
@@ -49,7 +49,7 @@ $ dvc pull
 The repository already contains the necessary configuration to run the
 experiments.
 
-## ⏲ Preparing a project for DVC experiments
+## 💡 Preparing a project for DVC experiments
 
 In this document we assume that there is already a configured DVC project to
 simplify the introduction. DVC experiments require a DVC pipeline defined in the
@@ -108,7 +108,7 @@ It runs the specified command that writes the metrics values to `metrics.json`.
 
 <details>
 
-### 📜 If you used `dvc repro` before
+### 📖 If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -128,7 +128,7 @@ not needed.
 
 </details>
 
-## 🧥 Running the experiment by setting parameters
+## ⏲ Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -328,7 +328,7 @@ You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
 running the experiment with the name starting with `exp-`, or the name you have
 supplied with `dvc exp run --name`.
 
-## 🪐 Go Further
+## ⭐ Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From f4dae657ce76478952c0e3978bb0e4261a6f0f43 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 10:54:16 +0300
Subject: [PATCH 70/89] removed the "note on experiments names" section

---
 .../start/experiments-trail/experiments.md    | 47 -------------------
 1 file changed, 47 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 09999c083d..1c8e3019b6 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -281,53 +281,6 @@ To switch to the new branch run:
 
 You can then checkout and continue from working this branch as usual.
 
-## 📛 Note on experiment names
-
-When you create an experiment, DVC generates a hash value from the contents of
-the experiment. This is shown when you use `--queue` option, e.g.,
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '6518f17' for future execution.
-```
-
-After _running_ the experiment, DVC uses another auto-generated name to refer to
-the experiment. Typically these start with `exp-`, and can be set via
-`--name / -n` option of `dvc exp run`. So when you add an experiment by setting
-the name, you can see the hash value as _queued experiment_:
-
-```dvc
-$ dvc exp run --queue --name cnn-512 -S model.conv_units=512
-Queued experiment '86bd8f9' for future execution.
-```
-
-In `dvc exp show` you can see both of these names:
-
-```dvc
-$ dvc exp show --no-pager --no-timestamp \
-      --include-metrics loss --include-params model.conv_units
-
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ Experiment              ┃ loss    ┃ model.conv_units ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.23534 │ 64               │
-│ 3973b6b                 │ -       │ 16               │
-│ ├── aeaabb0 [exp-cb13f] │ 0.23534 │ 64               │
-│ ├── d0ee7ce [exp-5dccf] │ 0.23818 │ 32               │
-│ ├── 1533e4d [exp-88874] │ 0.24039 │ 128              │
-│ ├── b1f41d3 [cnn-256]   │ 0.23296 │ 256              │
-│ ├── 07e927f [exp-6c06d] │ 0.23279 │ 24               │
-│ ├── b2b8586 [exp-2a1d5] │ 0.25036 │ 16               │
-│ └── *86bd8f9            │ -       │ 512              │
-└─────────────────────────┴─────────┴──────────────────┘
-```
-
-When an experiment is not run yet, only the former hash value is shown.
-
-You can refer to the experiment in `dvc exp apply` or `dvc exp branch` after
-running the experiment with the name starting with `exp-`, or the name you have
-supplied with `dvc exp run --name`.
-
 ## ⭐ Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused

From 77ff0c58e96872f46d09570cf086cd1a53718e69 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 10:55:08 +0300
Subject: [PATCH 71/89] removed "how dvc updates parameters" section

---
 .../start/experiments-trail/experiments.md    | 21 -------------------
 1 file changed, 21 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 1c8e3019b6..fd710b30e5 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -146,27 +146,6 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-### How DVC updates the parameters?
-
-When you run `dvc exp run` with `--set-param`, it updates the parameter file.
-(Default: `params.yaml`) We can see the effect of DVC updating the parameters by
-looking at the diff.
-
-```dvc
-$ git diff params.yaml
-```
-
-```git
--model:
--  conv_units: 16
-+model:
-+  conv_units: 24
-```
-
-</details>
-
-<details>
-
 ## 👟👟 Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a

From 397cc533450f9a0a2fa5b459783637f663fe7e20 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Thu, 19 Aug 2021 11:02:44 +0300
Subject: [PATCH 72/89] removed dvc exp apply

---
 .../start/experiments-trail/experiments.md    | 30 ++++---------------
 1 file changed, 5 insertions(+), 25 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index fd710b30e5..7572b25eaf 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -8,8 +8,8 @@ In machine learning projects, number of <abbr>experiments</abbr> grow rapidly.
 DVC can track these experiments, list their most relevant parameters and
 metrics, and commit only the ones that we need to Git.
 
-In this section, we will explore the basic features of DVC experiment management
-with [`get-started-experiments`][gse] project.
+In this section, we explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
 [gse]: https://github.com/iterative/get-started-experiments
 
@@ -80,7 +80,7 @@ change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
 experiment using `src/train.py` that produces a new `metrics.json` file.
 
 You can get more information on [pipelines], and [parameters] in other sections
-of this guide.
+of the documentation.
 
 [pipelines]: /doc/start/data-pipelines
 [parameters]: /doc/start/metrics-parameters-plots
@@ -227,28 +227,8 @@ $ dvc exp show --no-timestamp \
 
 ## 🔏 Persisting experiments
 
-After selecting an experiment from the table, you can commit the hyperparameters
-and other dependencies that produced this successful experiment to your Git
-history.
-
-`dvc exp apply` brings back all specific artifacts and parameters from the
-experiment to the <abbr>workspace</abbr>.
-
-```dvc
-$ dvc exp apply exp-cb13f
-Changes for experiment 'exp-cb13f' have been applied to your current workspace.
-```
-
-We can see the changes in the repository and commit them to Git.
-
-```dvc
-$ git diff
-$ git add .
-$ git commit -m "Successful experiment"
-```
-
-It may also be desirable to commit a particular experiment to a Git branch
-directly, without bringing to the workspace.
+After selecting an experiment from the table, you can create a Git branch that
+contains the experiment with all its related files.
 
 ```dvc
 $ dvc exp branch exp-05e87 "cnn-256"

From 065fa71ea8067a0dd324b0e9bfe83832fb744a9b Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 20 Aug 2021 13:24:46 +0300
Subject: [PATCH 73/89] removed screenshots

---
 static/img/start-dvc-exp-show-210704.png       | Bin 218492 -> 0 bytes
 .../start-dvc-exp-show-no-timestamp-210704.png | Bin 125016 -> 0 bytes
 2 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 static/img/start-dvc-exp-show-210704.png
 delete mode 100644 static/img/start-dvc-exp-show-no-timestamp-210704.png

diff --git a/static/img/start-dvc-exp-show-210704.png b/static/img/start-dvc-exp-show-210704.png
deleted file mode 100644
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From 5c2725b8c9014b130f47cdfdbcb9f22086b2d645 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Fri, 20 Aug 2021 14:22:59 +0300
Subject: [PATCH 74/89] edits for clarification

---
 .../start/experiments-trail/experiments.md    | 58 ++++++++++---------
 1 file changed, 31 insertions(+), 27 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 7572b25eaf..1e2eb91cfc 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -38,9 +38,8 @@ $ python -m pip install -r requirements.txt
 
 ### ✅ Get the data set
 
-The repository we cloned doesn't contain the dataset. In order to get the
-dataset we use `dvc pull` to update the missing data files. `dvc pull` is used
-in DVC repositories to update the missing data dependencies.
+The repository we cloned doesn't contain the dataset. We use `dvc pull` to
+update the missing data files.
 
 ```dvc
 $ dvc pull
@@ -51,11 +50,11 @@ experiments.
 
 ## 💡 Preparing a project for DVC experiments
 
-In this document we assume that there is already a configured DVC project to
-simplify the introduction. DVC experiments require a DVC pipeline defined in the
-project.
+If DVC is not installed to the system, please refer to [install](/doc/install).
 
-Please refer to [install](/doc/install) if DVC is not installed in your system.
+In this getting started page, we assume that there is already a configured DVC
+project to simplify the introduction. DVC experiments require a DVC pipeline
+defined in the project.
 
 If DVC is not initialized before in the project, you can do so by:
 
@@ -75,12 +74,13 @@ $ dvc stage add -n train \
                 python3 src/train.py
 ```
 
-The command tells DVC to create an experiment named `train`, and that for any
-change in `data/images/`, `model.conv_units` or `train.epochs`, we run an
-experiment using `src/train.py` that produces a new `metrics.json` file.
+The command tells DVC to create an experiment named `train`, and for any change
+in `data/images/` directory, `model.conv_units` or `train.epochs` parameters, we
+(re)run an experiment using `src/train.py` that produces a new `metrics.json`
+file.
 
-You can get more information on [pipelines], and [parameters] in other sections
-of the documentation.
+You can learn more about [pipelines], and [parameters] in other sections of the
+documentation.
 
 [pipelines]: /doc/start/data-pipelines
 [parameters]: /doc/start/metrics-parameters-plots
@@ -89,12 +89,12 @@ of the documentation.
 
 ## 👟 Running the experiment with default parameters
 
-The purpose of `dvc exp` subcommands is to run the pipeline for experiments
-without committing parameter and dependency changes to Git. Instead the
-artifacts produced for each experiment are tracked by DVC and persisted on
-demand.
+The purpose of `dvc exp` subcommands is to run the experiments without
+committing parameter and dependency changes to Git. The artifacts like models,
+metrics produced by each experiment are tracked by DVC and persisted on demand.
 
-Running the experiment with default project settings requires only the command:
+Running the experiment with the default project settings requires only the
+command:
 
 ```dvc
 $ dvc exp run
@@ -104,7 +104,12 @@ Experiment results have been applied to your workspace.
 ...
 ```
 
-It runs the specified command that writes the metrics values to `metrics.json`.
+It runs the specified command (`python train.py`) in `dvc.yaml`. That command
+writes the metrics values to `metrics.json`.
+
+This experiment is then associated with the values found in parameters file
+(`params.yaml`), and other dependencies (`data/images/`) with these produced
+metrics.
 
 <details>
 
@@ -113,15 +118,14 @@ It runs the specified command that writes the metrics values to `metrics.json`.
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
 
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. Both of these commands run the
-pipeline.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments. When you have large
-number of experiments that you don't want to commit all to Git, it's better to
-use `dvc exp run`. It allows to change the parameters quickly, can track the
-history of artifacts and has facilities to compare these experiments easily.
+In DVC 2.0 `dvc exp run` supersedes `dvc repro`. We use `dvc repro` to run the
+pipeline as found in the <abbr>workspace</abbr>. All the parameters and
+dependencies are retrieved from the current workspace. It doesn't use any
+special objects to track the experiments or associate parameters with metrics.
+When you have large number of experiments that you don't want to commit all to
+Git, it's better to use `dvc exp run`. It allows to change the parameters
+quickly, can track the history of artifacts and has facilities to compare these
+experiments easily.
 
 `dvc repro` is still available to run the pipeline when these extra features are
 not needed.

From b7d37dc3b5afd3252110a61bdef0cc2e18d7a654 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:17:27 +0300
Subject: [PATCH 75/89] revised the doc per reviews

---
 .../start/experiments-trail/experiments.md    | 65 ++++---------------
 1 file changed, 14 insertions(+), 51 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 1e2eb91cfc..cc5a8b0baa 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -4,9 +4,10 @@ title: 'Get Started: Experiments'
 
 # Get Started with Experiments
 
-In machine learning projects, number of <abbr>experiments</abbr> grow rapidly.
-DVC can track these experiments, list their most relevant parameters and
-metrics, and commit only the ones that we need to Git.
+In machine learning projects, the number of <abbr>experiments</abbr> grows
+rapidly. DVC can track these experiments, list and compare their most relevant
+parameters and metrics, navigate among them, and commit only the ones that we
+need to Git.
 
 In this section, we explore the basic features of DVC experiment management with
 [`get-started-experiments`][gse] project.
@@ -15,7 +16,7 @@ In this section, we explore the basic features of DVC experiment management with
 
 <details>
 
-## ⚙️ Installing the Example Project
+### ⚙️ Installing the Example Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
@@ -25,8 +26,8 @@ the requirements.
 
 Please clone the project and create a virtual environment.
 
-> We create a virtual environment to keep the libraries we use isolated from the
-> rest of your system. This prevents version conflicts.
+> We strongly recommend to create a virtual environment to keep the libraries we
+> use isolated from the rest of your system. This prevents version conflicts.
 
 ```dvc
 $ git clone https://github.com/iterative/get-started-experiments -b get-started
@@ -48,43 +49,6 @@ $ dvc pull
 The repository already contains the necessary configuration to run the
 experiments.
 
-## 💡 Preparing a project for DVC experiments
-
-If DVC is not installed to the system, please refer to [install](/doc/install).
-
-In this getting started page, we assume that there is already a configured DVC
-project to simplify the introduction. DVC experiments require a DVC pipeline
-defined in the project.
-
-If DVC is not initialized before in the project, you can do so by:
-
-```dvc
-$ dvc init
-```
-
-DVC also requires commands to be run and their dependencies to be defined as
-stages. We use `dvc stage add` to add a stage and set its dependencies.
-
-```dvc
-$ dvc stage add -n train \
-                -p model.conv_units \
-                -p train.epochs \
-                -d data/images \
-                -m metrics.json \
-                python3 src/train.py
-```
-
-The command tells DVC to create an experiment named `train`, and for any change
-in `data/images/` directory, `model.conv_units` or `train.epochs` parameters, we
-(re)run an experiment using `src/train.py` that produces a new `metrics.json`
-file.
-
-You can learn more about [pipelines], and [parameters] in other sections of the
-documentation.
-
-[pipelines]: /doc/start/data-pipelines
-[parameters]: /doc/start/metrics-parameters-plots
-
 </details>
 
 ## 👟 Running the experiment with default parameters
@@ -118,18 +82,16 @@ metrics.
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
 
-In DVC 2.0 `dvc exp run` supersedes `dvc repro`. We use `dvc repro` to run the
-pipeline as found in the <abbr>workspace</abbr>. All the parameters and
-dependencies are retrieved from the current workspace. It doesn't use any
-special objects to track the experiments or associate parameters with metrics.
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments or associate parameters
+with metrics.
+
 When you have large number of experiments that you don't want to commit all to
 Git, it's better to use `dvc exp run`. It allows to change the parameters
 quickly, can track the history of artifacts and has facilities to compare these
 experiments easily.
 
-`dvc repro` is still available to run the pipeline when these extra features are
-not needed.
-
 </details>
 
 ## ⏲ Running the experiment by setting parameters
@@ -242,7 +204,8 @@ To switch to the new branch run:
         git checkout cnn-256
 ```
 
-You can then checkout and continue from working this branch as usual.
+You can then checkout and continue working from this branch, or merge the branch
+your `main` branch with usual Git commands. .
 
 ## ⭐ Go Further
 

From 4e81e46d50bd6215bd19bebe3f7b385492300902 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:30:21 +0300
Subject: [PATCH 76/89] Update
 content/docs/start/experiments-trail/experiments.md

Co-authored-by: Julie <43496356+julieg18@users.noreply.github.com>
---
 content/docs/start/experiments-trail/experiments.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index cc5a8b0baa..36c77e9554 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -152,7 +152,7 @@ $ dvc exp show
 
 ```dvctable
 ┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ white:**Experiment**    ┃ white:**Created**┃    yellow:**loss** ┃    yellow:**acc** ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
 ┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
 │ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
 │ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │

From 02cd7028907fee05db7e54f4857284b6ef1154e0 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:41:51 +0300
Subject: [PATCH 77/89] minor edits

---
 content/docs/start/experiments-trail/experiments.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 36c77e9554..92ac9a275b 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -165,7 +165,7 @@ $ dvc exp show
 └─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
 ```
 
-By default it shows all the parameters and the metrics with the timestamp. If
+By default, it shows all the parameters and the metrics with the timestamp. If
 you have large number of parameters, metrics or experiments, this may lead to a
 cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
@@ -193,7 +193,8 @@ $ dvc exp show --no-timestamp \
 
 ## 🔏 Persisting experiments
 
-After selecting an experiment from the table, you can create a Git branch that
+After selecting an experiment from the table, it's possible to apply the
+experiment results to your workspace, or you can create a Git branch that
 contains the experiment with all its related files.
 
 ```dvc

From 62edbd88817c9b2036270bd7617cf1b9e14b71ea Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Mon, 4 Oct 2021 21:45:18 +0300
Subject: [PATCH 78/89] some emoji changes

---
 content/docs/start/experiments-trail/experiments.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 92ac9a275b..73622b84d7 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -51,7 +51,7 @@ experiments.
 
 </details>
 
-## 👟 Running the experiment with default parameters
+## ⚙️ Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the experiments without
 committing parameter and dependency changes to Git. The artifacts like models,
@@ -112,7 +112,7 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-## 👟👟 Run multiple experiments in parallel
+## ⚙️⚙️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -140,7 +140,7 @@ $ dvc exp run --run-all --jobs 2
 
 </details>
 
-## ↔️ Comparing experiments
+## 🙏️ Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the

From 10e6ec31362baa4de9159532fe23e73071ca5774 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:00:03 +0300
Subject: [PATCH 79/89] put the video

---
 content/docs/start/experiments-trail/experiments.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
index 73622b84d7..600e06b9e0 100644
--- a/content/docs/start/experiments-trail/experiments.md
+++ b/content/docs/start/experiments-trail/experiments.md
@@ -9,6 +9,8 @@ rapidly. DVC can track these experiments, list and compare their most relevant
 parameters and metrics, navigate among them, and commit only the ones that we
 need to Git.
 
+https://youtu.be/FHQq_zZz5ms
+
 In this section, we explore the basic features of DVC experiment management with
 [`get-started-experiments`][gse] project.
 

From bd4b6ad6d98763927564ec9959424c0292f62bc7 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:01:22 +0300
Subject: [PATCH 80/89] replaced older gs:experiments with the trail doc

---
 content/docs/sidebar.json                     |   4 +-
 .../start/experiments-trail/experiments.md    | 221 -----------
 content/docs/start/experiments.md             | 359 +++++++-----------
 3 files changed, 145 insertions(+), 439 deletions(-)
 delete mode 100644 content/docs/start/experiments-trail/experiments.md

diff --git a/content/docs/sidebar.json b/content/docs/sidebar.json
index c716a6319c..f63d316db3 100644
--- a/content/docs/sidebar.json
+++ b/content/docs/sidebar.json
@@ -60,8 +60,8 @@
         }
       },
       {
-        "slug": "experiments-trail/experiments",
-        "label": "Experiments Trail",
+        "slug": "experiments",
+        "label": "Experiments",
         "tutorials": {
           "katacoda": "https://katacoda.com/dvc/courses/get-started/experiments"
         }
diff --git a/content/docs/start/experiments-trail/experiments.md b/content/docs/start/experiments-trail/experiments.md
deleted file mode 100644
index 600e06b9e0..0000000000
--- a/content/docs/start/experiments-trail/experiments.md
+++ /dev/null
@@ -1,221 +0,0 @@
----
-title: 'Get Started: Experiments'
----
-
-# Get Started with Experiments
-
-In machine learning projects, the number of <abbr>experiments</abbr> grows
-rapidly. DVC can track these experiments, list and compare their most relevant
-parameters and metrics, navigate among them, and commit only the ones that we
-need to Git.
-
-https://youtu.be/FHQq_zZz5ms
-
-In this section, we explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
-
-[gse]: https://github.com/iterative/get-started-experiments
-
-<details>
-
-### ⚙️ Installing the Example Project
-
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
-
-### ⚡ Clone the project and create virtual environment
-
-Please clone the project and create a virtual environment.
-
-> We strongly recommend to create a virtual environment to keep the libraries we
-> use isolated from the rest of your system. This prevents version conflicts.
-
-```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b get-started
-$ cd get-started-experiments
-$ virtualenv .venv
-$ . .venv/bin/activate
-$ python -m pip install -r requirements.txt
-```
-
-### ✅ Get the data set
-
-The repository we cloned doesn't contain the dataset. We use `dvc pull` to
-update the missing data files.
-
-```dvc
-$ dvc pull
-```
-
-The repository already contains the necessary configuration to run the
-experiments.
-
-</details>
-
-## ⚙️ Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to run the experiments without
-committing parameter and dependency changes to Git. The artifacts like models,
-metrics produced by each experiment are tracked by DVC and persisted on demand.
-
-Running the experiment with the default project settings requires only the
-command:
-
-```dvc
-$ dvc exp run
-...
-Reproduced experiment(s): exp-b28f0
-Experiment results have been applied to your workspace.
-...
-```
-
-It runs the specified command (`python train.py`) in `dvc.yaml`. That command
-writes the metrics values to `metrics.json`.
-
-This experiment is then associated with the values found in parameters file
-(`params.yaml`), and other dependencies (`data/images/`) with these produced
-metrics.
-
-<details>
-
-### 📖 If you used `dvc repro` before
-
-Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
-have a DVC project, you may already be using `dvc repro`.
-
-We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
-All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments or associate parameters
-with metrics.
-
-When you have large number of experiments that you don't want to commit all to
-Git, it's better to use `dvc exp run`. It allows to change the parameters
-quickly, can track the history of artifacts and has facilities to compare these
-experiments easily.
-
-</details>
-
-## ⏲ Running the experiment by setting parameters
-
-Now let's do some more experimentation.
-
-DVC allows to update the parameters defined in the pipeline without modifying
-the files manually. We use this feature to set the convolutional units in
-`train.py`.
-
-```dvc
-$ dvc exp run --set-param model.conv_units=24
-...
-Reproduced experiment(s): exp-7b56f
-Experiment results have been applied to your workspace.
-...
-```
-
-<details>
-
-## ⚙️⚙️ Run multiple experiments in parallel
-
-Instead of running the experiments one-by-one, we can define them to run in a
-batch. This is especially handy when you have long running experiments.
-
-We add experiments to the queue using the `--queue` option of `dvc exp run`. We
-also use `-S` (`--set-param`) to set a value for the parameter.
-
-```dvc
-$ dvc exp run --queue -S model.conv_units=32
-Queued experiment '3cac8c6' for future execution.
-$ dvc exp run --queue -S model.conv_units=64
-Queued experiment '23660b6' for future execution.
-$ dvc exp run --queue -S model.conv_units=128
-Queued experiment '6591a57' for future execution.
-$ dvc exp run --queue -S model.conv_units=256
-Queued experiment '9109ea9' for future execution.
-```
-
-Next, run all (`--run-all`) queued experiments in parallel. You can specify the
-number of parallel processes using `--jobs`:
-
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
-
-</details>
-
-## 🙏️ Comparing experiments
-
-The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
-
-```dvc
-$ dvc exp show
-```
-
-```dvctable
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
-│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
-│ ├── e2647ef [exp-ee8a4] │ 05:14 PM     │ 0.23146 │ 0.9145 │ 10           │ 64               │
-│ ├── 15c9451 [exp-a9be6] │ 05:14 PM     │ 0.25231 │ 0.9102 │ 10           │ 32               │
-│ ├── 9c32227 [exp-17dd9] │ 04:46 PM     │ 0.23687 │ 0.9167 │ 10           │ 256              │
-│ ├── 8a9cb15 [exp-29d93] │ 04:46 PM     │ 0.24459 │ 0.9134 │ 10           │ 128              │
-│ ├── dfc536f [exp-a1bd9] │ 03:35 PM     │ 0.23508 │ 0.9151 │ 10           │ 24               │
-│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
-└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
-```
-
-By default, it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
-hide the timestamp column with `--include-metrics`, `--include-params`, or
-`--no-timestamp` options of the command, respectively.
-
-```dvc
-$ dvc exp show --no-timestamp \
-  --include-params model.conv_units --include-metrics acc
-```
-
-```dvctable
-┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
-┃ white:**Experiment**              ┃    yellow:**acc** ┃ blue:**model.conv_units** ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
-│ workspace               │ 0.9151 │ 24               │
-│ 7317bc6                 │      - │ 16               │
-│ ├── e2647ef [exp-ee8a4] │ 0.9145 │ 64               │
-│ ├── 15c9451 [exp-a9be6] │ 0.9102 │ 32               │
-│ ├── 9c32227 [exp-17dd9] │ 0.9167 │ 256              │
-│ ├── 8a9cb15 [exp-29d93] │ 0.9134 │ 128              │
-│ ├── dfc536f [exp-a1bd9] │ 0.9151 │ 24               │
-│ └── 1a1d858 [exp-6dccf] │ 0.9152 │ 16               │
-└─────────────────────────┴────────┴──────────────────┘
-```
-
-## 🔏 Persisting experiments
-
-After selecting an experiment from the table, it's possible to apply the
-experiment results to your workspace, or you can create a Git branch that
-contains the experiment with all its related files.
-
-```dvc
-$ dvc exp branch exp-05e87 "cnn-256"
-Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
-To switch to the new branch run:
-
-        git checkout cnn-256
-```
-
-You can then checkout and continue working from this branch, or merge the branch
-your `main` branch with usual Git commands. .
-
-## ⭐ Go Further
-
-There are many other features of `dvc exp`, like cleaning up the unused
-experiments, sharing them without committing into Git or getting differences
-between two experiments.
-
-Please see the section on
-[Experiment Management](/doc/user-guide/experiment-management) in the User's
-Guide or `dvc exp` and subcommands in the Command Reference.
diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 13568927da..600e06b9e0 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -2,293 +2,220 @@
 title: 'Get Started: Experiments'
 ---
 
-# Get Started: Experiments
+# Get Started with Experiments
 
-_New in DVC 2.0_
-
-<abbr>Experiments</abbr> proliferate quickly in ML projects where there are many
-parameters to tune or other permutations of the code. We can organize such
-projects and keep only what we ultimately need with `dvc exp` commands. DVC can
-track experiments for you so there's no need to commit each one to Git. This way
-your repo doesn't become polluted with all of them. You can discard experiments
-once they're no longer needed.
-
-> 📖 See [Experiment Management](/doc/user-guide/experiment-management) for more
-> information on DVC's approach.
+In machine learning projects, the number of <abbr>experiments</abbr> grows
+rapidly. DVC can track these experiments, list and compare their most relevant
+parameters and metrics, navigate among them, and commit only the ones that we
+need to Git.
 
 https://youtu.be/FHQq_zZz5ms
 
-## Running experiments
+In this section, we explore the basic features of DVC experiment management with
+[`get-started-experiments`][gse] project.
 
-Previously, we learned how to tune [ML pipelines](/doc/start/data-pipelines) and
-[compare the changes](/doc/start/metrics-parameters-plots). Let's further
-increase the number of features in the `featurize` stage to see how it compares.
-
-`dvc exp run` makes it easy to change <abbr>hyperparameters</abbr> and run a new
-experiment:
-
-```dvc
-$ dvc exp run --set-param featurize.max_features=3000
-```
+[gse]: https://github.com/iterative/get-started-experiments
 
 <details>
 
-### 💡 Expand to see what happens under the hood.
-
-`dvc exp run` is similar to `dvc repro` but with some added conveniences for
-running experiments. The `--set-param` (or `-S`) flag sets the values for
-<abbr>parameters<abbr> as a shortcut for editing `params.yaml`.
+### ⚙️ Installing the Example Project
 
-Check that the `featurize.max_features` value has been updated in `params.yaml`:
+These commands are run in the [`get-started-experiments`][gse] project. You can
+run the commands in this document after cloning the repository and installing
+the requirements.
 
-```git
- featurize:
--  max_features: 1500
-+  max_features: 3000
-```
-
-Any edits to <abbr>dependencies</abbr> (parameters or source code) will be
-reflected in the experiment run.
+### ⚡ Clone the project and create virtual environment
 
-</details>
+Please clone the project and create a virtual environment.
 
-`dvc exp diff` compares experiments:
+> We strongly recommend to create a virtual environment to keep the libraries we
+> use isolated from the rest of your system. This prevents version conflicts.
 
 ```dvc
-$ dvc exp diff
-Path         Metric    Value    Change
-scores.json  avg_prec  0.56191  0.009322
-scores.json  roc_auc   0.93345  0.018087
-
-Path         Param                   Value    Change
-params.yaml  featurize.max_features  3000     1500
+$ git clone https://github.com/iterative/get-started-experiments -b get-started
+$ cd get-started-experiments
+$ virtualenv .venv
+$ . .venv/bin/activate
+$ python -m pip install -r requirements.txt
 ```
 
-## Queueing experiments
+### ✅ Get the data set
 
-So far, we have been tuning the `featurize` stage, but there are also parameters
-for the `train` stage (which trains a
-[random forest classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)).
-
-These are the `train` parameters from `params.yaml`:
-
-```yaml
-train:
-  seed: 20170428
-  n_est: 50
-  min_split: 2
-```
-
-Let's set up experiments with different hyperparameters. We can use the
-`--queue` flag to define all the combinations we want to try without executing
-anything (yet):
+The repository we cloned doesn't contain the dataset. We use `dvc pull` to
+update the missing data files.
 
 ```dvc
-$ dvc exp run --queue -S train.min_split=8
-Queued experiment 'd3f6d1e' for future execution.
-$ dvc exp run --queue -S train.min_split=64
-Queued experiment 'f1810e0' for future execution.
-$ dvc exp run --queue -S train.min_split=2 -S train.n_est=100
-Queued experiment '7323ea2' for future execution.
-$ dvc exp run --queue -S train.min_split=8 -S train.n_est=100
-Queued experiment 'c605382' for future execution.
-$ dvc exp run --queue -S train.min_split=64 -S train.n_est=100
-Queued experiment '0cdee86' for future execution.
+$ dvc pull
 ```
 
-Next, run all (`--run-all`) queued experiments in parallel (using `--jobs`):
+The repository already contains the necessary configuration to run the
+experiments.
 
-```dvc
-$ dvc exp run --run-all --jobs 2
-```
+</details>
 
-## Comparing many experiments
+## ⚙️ Running the experiment with default parameters
 
-To compare all of these experiments, we need more than `diff`. `dvc exp show`
-compares any number of experiments in one table:
+The purpose of `dvc exp` subcommands is to run the experiments without
+committing parameter and dependency changes to Git. The artifacts like models,
+metrics produced by each experiment are tracked by DVC and persisted on demand.
 
-```dvc
-$ dvc exp show --no-timestamp \
-               --include-params train.n_est,train.min_split
-```
+Running the experiment with the default project settings requires only the
+command:
 
-```dvctable
-┏━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment**    ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**     │  **0.56191** │ **0.93345** │ **50**         │ **2**               │
-│ **master**        │  **0.55259** │ **0.91536** │ **50**         │ **2**               │
-│ ├── exp-bfe64 │  0.57833 │ 0.95555 │ 50         │ 8               │
-│ ├── exp-b8082 │  0.59806 │ 0.95287 │ 50         │ 64              │
-│ ├── exp-c7250 │  0.58876 │ 0.94524 │ 100        │ 2               │
-│ ├── exp-b9cd4 │  0.57953 │ 0.95732 │ 100        │ 8               │
-│ ├── exp-98a96 │  0.60405 │  0.9608 │ 100        │ 64              │
-│ └── exp-ad5b1 │  0.56191 │ 0.93345 │ 50         │ 2               │
-└───────────────┴──────────┴─────────┴────────────┴─────────────────┘
+```dvc
+$ dvc exp run
+...
+Reproduced experiment(s): exp-b28f0
+Experiment results have been applied to your workspace.
+...
 ```
 
-Each experiment is given an arbitrary name by default (although we can specify
-one with `dvc exp run -n`.) We can see that `exp-98a96` performed best among
-both of our metrics, with 100 estimators and a minimum of 64 samples to split a
-node.
-
-> See `dvc exp show --help` for more info on its options.
-
-## Persisting experiments
-
-Now that we know the best parameters, let's keep that experiment and ignore the
-rest.
+It runs the specified command (`python train.py`) in `dvc.yaml`. That command
+writes the metrics values to `metrics.json`.
 
-`dvc exp apply` rolls back the <abbr>workspace<abbr> to the specified
-experiment:
-
-```dvc
-$ dvc exp apply exp-98a96
-Changes for experiment 'exp-98a96' have been applied to your workspace.
-```
+This experiment is then associated with the values found in parameters file
+(`params.yaml`), and other dependencies (`data/images/`) with these produced
+metrics.
 
 <details>
 
-### 💡 Expand to see what happens under the hood.
+### 📖 If you used `dvc repro` before
 
-`dvc exp apply` is similar to `dvc checkout`, but works with experiments
-instead. DVC tracks everything in the pipeline for each experiment (parameters,
-metrics, dependencies, and outputs), retrieving things later as needed.
+Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
+have a DVC project, you may already be using `dvc repro`.
 
-Check that `scores.json` reflects the metrics in the table above:
+We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
+All the parameters and dependencies are retrieved from the current workspace. It
+doesn't use any special objects to track the experiments or associate parameters
+with metrics.
 
-```json
-{ "avg_prec": 0.6040544652105823, "roc_auc": 0.9608017142900953 }
-```
+When you have large number of experiments that you don't want to commit all to
+Git, it's better to use `dvc exp run`. It allows to change the parameters
+quickly, can track the history of artifacts and has facilities to compare these
+experiments easily.
 
 </details>
 
-Once an experiment has been applied to the workspace, it is no different from
-reproducing the result without `dvc exp run`. Let's make it persistent in our
-regular pipeline by committing it in our Git branch:
-
-```dvc
-$ git add dvc.lock params.yaml prc.json roc.json scores.json
-$ git commit -a -m "Preserve best random forest experiment"
-```
+## ⏲ Running the experiment by setting parameters
 
-## Sharing experiments
+Now let's do some more experimentation.
 
-After committing the best experiments to our Git branch, we can
-[store and share](/doc/start/data-and-model-versioning#storing-and-sharing) them
-remotely like any other iteration of the pipeline.
+DVC allows to update the parameters defined in the pipeline without modifying
+the files manually. We use this feature to set the convolutional units in
+`train.py`.
 
 ```dvc
-dvc push
-git push
+$ dvc exp run --set-param model.conv_units=24
+...
+Reproduced experiment(s): exp-7b56f
+Experiment results have been applied to your workspace.
+...
 ```
 
 <details>
 
-### 💡 Important information on storing experiments remotely.
+## ⚙️⚙️ Run multiple experiments in parallel
 
-The commands in this section require both a `dvc remote default` and a
-[Git remote](https://git-scm.com/book/en/v2/Git-Basics-Working-with-Remotes). A
-DVC remote stores the experiment data, and a Git remote stores the code,
-parameters, and other metadata associated with the experiment. DVC supports
-various types of remote storage (local file system, SSH, Amazon S3, Google Cloud
-Storage, HTTP, HDFS, etc.). The Git remote is often a central Git server
-(GitHub, GitLab, BitBucket, etc.).
+Instead of running the experiments one-by-one, we can define them to run in a
+batch. This is especially handy when you have long running experiments.
 
-</details>
-
-Experiments that have not been made persistent will not be stored or shared
-remotely through `dvc push` or `git push`.
-
-`dvc exp push` enables storing and sharing any experiment remotely.
+We add experiments to the queue using the `--queue` option of `dvc exp run`. We
+also use `-S` (`--set-param`) to set a value for the parameter.
 
 ```dvc
-$ dvc exp push gitremote exp-bfe64
-Pushed experiment 'exp-bfe64' to Git remote 'gitremote'.
+$ dvc exp run --queue -S model.conv_units=32
+Queued experiment '3cac8c6' for future execution.
+$ dvc exp run --queue -S model.conv_units=64
+Queued experiment '23660b6' for future execution.
+$ dvc exp run --queue -S model.conv_units=128
+Queued experiment '6591a57' for future execution.
+$ dvc exp run --queue -S model.conv_units=256
+Queued experiment '9109ea9' for future execution.
 ```
 
-`dvc exp list` shows all experiments that have been saved.
+Next, run all (`--run-all`) queued experiments in parallel. You can specify the
+number of parallel processes using `--jobs`:
 
 ```dvc
-$ dvc exp list gitremote --all
-72ed9cd:
-        exp-bfe64
+$ dvc exp run --run-all --jobs 2
 ```
 
-`dvc exp pull` retrieves the experiment from a Git remote.
+</details>
 
-```dvc
-$ dvc exp pull gitremote exp-bfe64
-Pulled experiment 'exp-bfe64' from Git remote 'gitremote'.
-```
+## 🙏️ Comparing experiments
 
-> All these commands take a Git remote as an argument. A `dvc remote default` is
-> also required to share the experiment data.
+The experiments are run several times with different parameters. We use
+`dvc exp show` to compare all of these experiments. This command presents the
+parameters and metrics produced in experiments in a nicely formatted table.
 
-## Cleaning up
+```dvc
+$ dvc exp show
+```
 
-Let's take another look at the experiments table:
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ -            │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 05:14 PM     │ 0.23146 │ 0.9145 │ 10           │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 05:14 PM     │ 0.25231 │ 0.9102 │ 10           │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 04:46 PM     │ 0.23687 │ 0.9167 │ 10           │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 04:46 PM     │ 0.24459 │ 0.9134 │ 10           │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 03:35 PM     │ 0.23508 │ 0.9151 │ 10           │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
+└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
+```
+
+By default, it shows all the parameters and the metrics with the timestamp. If
+you have large number of parameters, metrics or experiments, this may lead to a
+cluttered view. You can limit the table to specific metrics, or parameters, or
+hide the timestamp column with `--include-metrics`, `--include-params`, or
+`--no-timestamp` options of the command, respectively.
 
 ```dvc
 $ dvc exp show --no-timestamp \
-               --include-params train.n_est,train.min_split
+  --include-params model.conv_units --include-metrics acc
 ```
 
 ```dvctable
-┏━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment** ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**  │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **master**     │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-└────────────┴──────────┴─────────┴────────────┴─────────────────┘
-```
-
-Where did all the experiments go? By default, `dvc exp show` only shows
-experiments since the last commit, but don't worry. The experiments remain
-<abbr>cached</abbr> and can be shown or applied. For example, use `-n` to show
-experiments from the previous _n_ commits:
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃    yellow:**acc** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ 0.9151 │ 24               │
+│ 7317bc6                 │      - │ 16               │
+│ ├── e2647ef [exp-ee8a4] │ 0.9145 │ 64               │
+│ ├── 15c9451 [exp-a9be6] │ 0.9102 │ 32               │
+│ ├── 9c32227 [exp-17dd9] │ 0.9167 │ 256              │
+│ ├── 8a9cb15 [exp-29d93] │ 0.9134 │ 128              │
+│ ├── dfc536f [exp-a1bd9] │ 0.9151 │ 24               │
+│ └── 1a1d858 [exp-6dccf] │ 0.9152 │ 16               │
+└─────────────────────────┴────────┴──────────────────┘
+```
+
+## 🔏 Persisting experiments
+
+After selecting an experiment from the table, it's possible to apply the
+experiment results to your workspace, or you can create a Git branch that
+contains the experiment with all its related files.
 
 ```dvc
-$ dvc exp show -n 2 --no-timestamp \
-                    --include-params train.n_est,train.min_split
-```
+$ dvc exp branch exp-05e87 "cnn-256"
+Git branch 'cnn-256' has been created from experiment 'exp-05e87'.
+To switch to the new branch run:
 
-```dvctable
-┏━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment**    ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**     │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **master**        │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **64d74b2**       │  **0.55259** │ **0.91536** │ **50**         │ **2**               │
-│ ├── exp-bfe64 │  0.57833 │ 0.95555 │ 50         │ 8               │
-│ ├── exp-b8082 │  0.59806 │ 0.95287 │ 50         │ 64              │
-│ ├── exp-c7250 │  0.58876 │ 0.94524 │ 100        │ 2               │
-│ ├── exp-98a96 │  0.60405 │  0.9608 │ 100        │ 64              │
-│ ├── exp-b9cd4 │  0.57953 │ 0.95732 │ 100        │ 8               │
-│ └── exp-ad5b1 │  0.56191 │ 0.93345 │ 50         │ 2               │
-└───────────────┴──────────┴─────────┴────────────┴─────────────────┘
+        git checkout cnn-256
 ```
 
-Eventually, old experiments may clutter the experiments table.
-
-`dvc exp gc` removes all references to old experiments:
+You can then checkout and continue working from this branch, or merge the branch
+your `main` branch with usual Git commands. .
 
-```dvc
-$ dvc exp gc --workspace
-$ dvc exp show -n 2 --no-timestamp \
-                    --include-params train.n_est,train.min_split
-```
+## ⭐ Go Further
 
-```dvctable
-┏━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
-┃ neutral:**Experiment** ┃ metric:**avg_prec** ┃ metric:**roc_auc** ┃ param:**train.n_est**┃ param:**train.min_split** ┃
-┡━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
-│ **workspace**  │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **master**     │  **0.60405** │  **0.9608** │ **100**        │ **64**              │
-│ **64d74b2**    │  **0.55259** │ **0.91536** │ **50**         │ **2**               │
-└────────────┴──────────┴─────────┴────────────┴─────────────────┘
-```
+There are many other features of `dvc exp`, like cleaning up the unused
+experiments, sharing them without committing into Git or getting differences
+between two experiments.
 
-> `dvc exp gc` only removes references to the experiments; not the cached
-> objects associated with them. To clean up the <abbr>cache</abbr>, use
-> `dvc gc`.
+Please see the section on
+[Experiment Management](/doc/user-guide/experiment-management) in the User's
+Guide or `dvc exp` and subcommands in the Command Reference.

From 8dfe709160d9a260c994b2930b8eaa87fbdec249 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:12:05 +0300
Subject: [PATCH 81/89] Removed emoji and moved persisting to details section

---
 content/docs/start/experiments.md | 26 +++++++++++++++-----------
 1 file changed, 15 insertions(+), 11 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 600e06b9e0..89b9d62847 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -18,13 +18,13 @@ In this section, we explore the basic features of DVC experiment management with
 
 <details>
 
-### ⚙️ Installing the Example Project
+### Installing the Example Project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
 the requirements.
 
-### ⚡ Clone the project and create virtual environment
+#### Clone the project and create virtual environment
 
 Please clone the project and create a virtual environment.
 
@@ -39,7 +39,7 @@ $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
 ```
 
-### ✅ Get the data set
+#### Get the data set
 
 The repository we cloned doesn't contain the dataset. We use `dvc pull` to
 update the missing data files.
@@ -53,7 +53,7 @@ experiments.
 
 </details>
 
-## ⚙️ Running the experiment with default parameters
+## Running the experiment with default parameters
 
 The purpose of `dvc exp` subcommands is to run the experiments without
 committing parameter and dependency changes to Git. The artifacts like models,
@@ -79,7 +79,7 @@ metrics.
 
 <details>
 
-### 📖 If you used `dvc repro` before
+### If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -96,7 +96,7 @@ experiments easily.
 
 </details>
 
-## ⏲ Running the experiment by setting parameters
+## Running the experiment by setting parameters
 
 Now let's do some more experimentation.
 
@@ -114,7 +114,7 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-## ⚙️⚙️ Run multiple experiments in parallel
+### Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -142,7 +142,7 @@ $ dvc exp run --run-all --jobs 2
 
 </details>
 
-## 🙏️ Comparing experiments
+## Comparing experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -193,7 +193,9 @@ $ dvc exp show --no-timestamp \
 └─────────────────────────┴────────┴──────────────────┘
 ```
 
-## 🔏 Persisting experiments
+<details>
+
+### Persisting experiments
 
 After selecting an experiment from the table, it's possible to apply the
 experiment results to your workspace, or you can create a Git branch that
@@ -208,9 +210,11 @@ To switch to the new branch run:
 ```
 
 You can then checkout and continue working from this branch, or merge the branch
-your `main` branch with usual Git commands. .
+your `main` branch with usual Git commands.
+
+</details>
 
-## ⭐ Go Further
+## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused
 experiments, sharing them without committing into Git or getting differences

From 56ccd4c9d194ba736bcf9bd0369aa71191586be4 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Tue, 5 Oct 2021 17:24:56 +0300
Subject: [PATCH 82/89] added a sentence for data management

---
 content/docs/start/experiments.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 89b9d62847..8a66e66cec 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -41,8 +41,9 @@ $ python -m pip install -r requirements.txt
 
 #### Get the data set
 
-The repository we cloned doesn't contain the dataset. We use `dvc pull` to
-update the missing data files.
+The repository we cloned doesn't contain the dataset. Instead of storing the
+data in Git repository, we use DVC to retrieve from a shared data store. In this
+case, we use `dvc pull` to update the missing data files.
 
 ```dvc
 $ dvc pull

From 2a8b42edd88e49ce77a57782619cfdd50f947cc8 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Wed, 6 Oct 2021 14:12:15 +0300
Subject: [PATCH 83/89] added a brief `dvc exp show` after the first run.

---
 content/docs/start/experiments.md | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 8a66e66cec..d2de3621ec 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -78,6 +78,26 @@ This experiment is then associated with the values found in parameters file
 (`params.yaml`), and other dependencies (`data/images/`) with these produced
 metrics.
 
+You can review the experiment results with `dvc exp show` and see these metrics
+and results in a nicely formatted table:
+
+```dvc
+$ dvc exp show
+```
+
+```dvctable
+┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┓
+┃ white:**Experiment**              ┃ white:**Created**      ┃ yellow:**loss**    ┃ yellow:**acc**    ┃ blue:**train.epochs** ┃ blue:**model.conv_units** ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━┩
+│ workspace               │ -            │ 0.23282 │ 0.9152 │ 10           │ 16               │
+│ 7317bc6                 │ Jul 18, 2021 │       - │      - │ 10           │ 16               │
+│ └── 1a1d858 [exp-6dccf] │ 03:21 PM     │ 0.23282 │ 0.9152 │ 10           │ 16               │
+└─────────────────────────┴──────────────┴─────────┴────────┴──────────────┴──────────────────┘
+```
+
+The `workspace` row in the table shows the results of the most recent experiment
+that's available in the <bbr>workspace</abbr>.
+
 <details>
 
 ### If you used `dvc repro` before

From 769c2e6af6fed1ee2b7bbd2dd2147b7c51d4f892 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Wed, 6 Oct 2021 14:16:25 +0300
Subject: [PATCH 84/89] added emoji to detail headers

---
 content/docs/start/experiments.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index d2de3621ec..3b47f8ca7a 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -18,7 +18,7 @@ In this section, we explore the basic features of DVC experiment management with
 
 <details>
 
-### Installing the Example Project
+### ⚙️ Installing the example project
 
 These commands are run in the [`get-started-experiments`][gse] project. You can
 run the commands in this document after cloning the repository and installing
@@ -100,7 +100,7 @@ that's available in the <bbr>workspace</abbr>.
 
 <details>
 
-### If you used `dvc repro` before
+### ℹ️ If you used `dvc repro` before
 
 Earlier versions of DVC uses `dvc repro` to run the pipeline. If you already
 have a DVC project, you may already be using `dvc repro`.
@@ -135,7 +135,7 @@ Experiment results have been applied to your workspace.
 
 <details>
 
-### Run multiple experiments in parallel
+### ⚙️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a
 batch. This is especially handy when you have long running experiments.
@@ -216,7 +216,7 @@ $ dvc exp show --no-timestamp \
 
 <details>
 
-### Persisting experiments
+### ✅ Persisting experiments
 
 After selecting an experiment from the table, it's possible to apply the
 experiment results to your workspace, or you can create a Git branch that

From c7ddcf8b9dba0709419c2f763365aebd1d977717 Mon Sep 17 00:00:00 2001
From: Emre Sahin <github@emresult.com>
Date: Wed, 6 Oct 2021 14:26:44 +0300
Subject: [PATCH 85/89] added an initial text

---
 content/docs/start/experiments.md | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 3b47f8ca7a..9edbf6c8b3 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -56,9 +56,11 @@ experiments.
 
 ## Running the experiment with default parameters
 
-The purpose of `dvc exp` subcommands is to run the experiments without
-committing parameter and dependency changes to Git. The artifacts like models,
-metrics produced by each experiment are tracked by DVC and persisted on demand.
+The purpose of `dvc exp` subcommands is to let you run, capture, compare the
+machine learning experiments at once as you iterate on your code, data, and
+hyperparameters. The artifacts like models, metrics produced by each experiment
+are tracked by DVC and the associated parameters and metrics can be committed to
+Git as text files.
 
 Running the experiment with the default project settings requires only the
 command:

From 915c61a37875470c460039a09c9436e3e8ca96be Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Fri, 8 Oct 2021 16:44:36 +0300
Subject: [PATCH 86/89] some suggestions of Ivan applied.

---
 content/docs/start/experiments.md | 29 +++++++++++------------------
 1 file changed, 11 insertions(+), 18 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 9edbf6c8b3..1f3bf4f003 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -54,14 +54,6 @@ experiments.
 
 </details>
 
-## Running the experiment with default parameters
-
-The purpose of `dvc exp` subcommands is to let you run, capture, compare the
-machine learning experiments at once as you iterate on your code, data, and
-hyperparameters. The artifacts like models, metrics produced by each experiment
-are tracked by DVC and the associated parameters and metrics can be committed to
-Git as text files.
-
 Running the experiment with the default project settings requires only the
 command:
 
@@ -80,6 +72,12 @@ This experiment is then associated with the values found in parameters file
 (`params.yaml`), and other dependencies (`data/images/`) with these produced
 metrics.
 
+The purpose of `dvc exp` family of commands is to let you run, capture, compare
+the machine learning experiments at once as you iterate on your code, data,
+models, and hyperparameters. The artifacts like models, metrics produced by each
+experiment are tracked by DVC and the associated parameters and metrics can be
+committed to Git as text files.
+
 You can review the experiment results with `dvc exp show` and see these metrics
 and results in a nicely formatted table:
 
@@ -98,7 +96,10 @@ $ dvc exp show
 ```
 
 The `workspace` row in the table shows the results of the most recent experiment
-that's available in the <bbr>workspace</abbr>.
+that's available in the <bbr>workspace</abbr>. The table also shows each
+experiment in a separate row, along with the Git commit IDs they are attached
+to. We can see that the experiment we run has a name `exp-6dccf` and run from
+the commit ID `7317bc6`.
 
 <details>
 
@@ -119,8 +120,6 @@ experiments easily.
 
 </details>
 
-## Running the experiment by setting parameters
-
 Now let's do some more experimentation.
 
 DVC allows to update the parameters defined in the pipeline without modifying
@@ -165,7 +164,7 @@ $ dvc exp run --run-all --jobs 2
 
 </details>
 
-## Comparing experiments
+## Comparing and persisting experiments
 
 The experiments are run several times with different parameters. We use
 `dvc exp show` to compare all of these experiments. This command presents the
@@ -216,10 +215,6 @@ $ dvc exp show --no-timestamp \
 └─────────────────────────┴────────┴──────────────────┘
 ```
 
-<details>
-
-### ✅ Persisting experiments
-
 After selecting an experiment from the table, it's possible to apply the
 experiment results to your workspace, or you can create a Git branch that
 contains the experiment with all its related files.
@@ -235,8 +230,6 @@ To switch to the new branch run:
 You can then checkout and continue working from this branch, or merge the branch
 your `main` branch with usual Git commands.
 
-</details>
-
 ## Go Further
 
 There are many other features of `dvc exp`, like cleaning up the unused

From ea94da60abc84c4b8236b71b4dc085a2a597e042 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Fri, 15 Oct 2021 20:02:06 +0300
Subject: [PATCH 87/89] modifications after Dave's review

---
 content/docs/start/experiments.md | 41 ++++++++++++++-----------------
 1 file changed, 19 insertions(+), 22 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 1f3bf4f003..543a108154 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -12,17 +12,17 @@ need to Git.
 https://youtu.be/FHQq_zZz5ms
 
 In this section, we explore the basic features of DVC experiment management with
-[`get-started-experiments`][gse] project.
+the [`example-dvc-experiments`][ede] project.
 
-[gse]: https://github.com/iterative/get-started-experiments
+[ede]: https://github.com/iterative/example-dvc-experiments
 
 <details>
 
 ### ⚙️ Installing the example project
 
-These commands are run in the [`get-started-experiments`][gse] project. You can
-run the commands in this document after cloning the repository and installing
-the requirements.
+These commands are run in the [`example-dvc-experiments`][ede] project. You can
+run the commands in this document after cloning the repository, installing the
+requirements, and pulling the data.
 
 #### Clone the project and create virtual environment
 
@@ -32,8 +32,8 @@ Please clone the project and create a virtual environment.
 > use isolated from the rest of your system. This prevents version conflicts.
 
 ```dvc
-$ git clone https://github.com/iterative/get-started-experiments -b get-started
-$ cd get-started-experiments
+$ git clone https://github.com/iterative/example-dvc-experiments -b get-started
+$ cd example-dvc-experiments
 $ virtualenv .venv
 $ . .venv/bin/activate
 $ python -m pip install -r requirements.txt
@@ -72,11 +72,11 @@ This experiment is then associated with the values found in parameters file
 (`params.yaml`), and other dependencies (`data/images/`) with these produced
 metrics.
 
-The purpose of `dvc exp` family of commands is to let you run, capture, compare
-the machine learning experiments at once as you iterate on your code, data,
-models, and hyperparameters. The artifacts like models, metrics produced by each
-experiment are tracked by DVC and the associated parameters and metrics can be
-committed to Git as text files.
+The purpose of the `dvc exp` family of commands is to let you run, capture, and
+compare the machine learning experiments at once as you iterate on your project.
+The artifacts like models and metrics produced by each experiment are tracked by
+DVC, and the associated parameters and metrics can be committed to Git as text
+files.
 
 You can review the experiment results with `dvc exp show` and see these metrics
 and results in a nicely formatted table:
@@ -110,10 +110,9 @@ have a DVC project, you may already be using `dvc repro`.
 
 We use `dvc repro` to run the pipeline as found in the <abbr>workspace</abbr>.
 All the parameters and dependencies are retrieved from the current workspace. It
-doesn't use any special objects to track the experiments or associate parameters
-with metrics.
+doesn't use any specialized mechanism to track experiments.
 
-When you have large number of experiments that you don't want to commit all to
+When you have a large number of experiments that you don't want to commit all to
 Git, it's better to use `dvc exp run`. It allows to change the parameters
 quickly, can track the history of artifacts and has facilities to compare these
 experiments easily.
@@ -167,8 +166,7 @@ $ dvc exp run --run-all --jobs 2
 ## Comparing and persisting experiments
 
 The experiments are run several times with different parameters. We use
-`dvc exp show` to compare all of these experiments. This command presents the
-parameters and metrics produced in experiments in a nicely formatted table.
+`dvc exp show` to compare all of these experiments.
 
 ```dvc
 $ dvc exp show
@@ -190,8 +188,8 @@ $ dvc exp show
 ```
 
 By default, it shows all the parameters and the metrics with the timestamp. If
-you have large number of parameters, metrics or experiments, this may lead to a
-cluttered view. You can limit the table to specific metrics, or parameters, or
+you have a large number of parameters, metrics or experiments, this may lead to
+a cluttered view. You can limit the table to specific metrics, or parameters, or
 hide the timestamp column with `--include-metrics`, `--include-params`, or
 `--no-timestamp` options of the command, respectively.
 
@@ -215,8 +213,7 @@ $ dvc exp show --no-timestamp \
 └─────────────────────────┴────────┴──────────────────┘
 ```
 
-After selecting an experiment from the table, it's possible to apply the
-experiment results to your workspace, or you can create a Git branch that
+After selecting an experiment from the table you can create a Git branch that
 contains the experiment with all its related files.
 
 ```dvc
@@ -228,7 +225,7 @@ To switch to the new branch run:
 ```
 
 You can then checkout and continue working from this branch, or merge the branch
-your `main` branch with usual Git commands.
+into your `main` branch with the usual Git commands.
 
 ## Go Further
 

From ec3d13243feddf55468d00ccc82498b718995d11 Mon Sep 17 00:00:00 2001
From: Emre Sahin <emre@iterative.ai>
Date: Fri, 15 Oct 2021 20:06:25 +0300
Subject: [PATCH 88/89] merged


From d3cae7a71c8de6e7f60c2041ded614430f3bdafa Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Emre=20=C5=9Eahin?= <github@emresult.com>
Date: Mon, 18 Oct 2021 17:55:31 +0300
Subject: [PATCH 89/89] revised after Dave's review.

---
 content/docs/start/experiments.md | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/content/docs/start/experiments.md b/content/docs/start/experiments.md
index 543a108154..c23058b319 100644
--- a/content/docs/start/experiments.md
+++ b/content/docs/start/experiments.md
@@ -42,8 +42,8 @@ $ python -m pip install -r requirements.txt
 #### Get the data set
 
 The repository we cloned doesn't contain the dataset. Instead of storing the
-data in Git repository, we use DVC to retrieve from a shared data store. In this
-case, we use `dvc pull` to update the missing data files.
+data in the Git repository, we use DVC to retrieve from a shared data store. In
+this case, we use `dvc pull` to update the missing data files.
 
 ```dvc
 $ dvc pull
@@ -68,7 +68,7 @@ Experiment results have been applied to your workspace.
 It runs the specified command (`python train.py`) in `dvc.yaml`. That command
 writes the metrics values to `metrics.json`.
 
-This experiment is then associated with the values found in parameters file
+This experiment is then associated with the values found in the parameters file
 (`params.yaml`), and other dependencies (`data/images/`) with these produced
 metrics.
 
@@ -96,10 +96,10 @@ $ dvc exp show
 ```
 
 The `workspace` row in the table shows the results of the most recent experiment
-that's available in the <bbr>workspace</abbr>. The table also shows each
+that's available in the <abbr>workspace</abbr>. The table also shows each
 experiment in a separate row, along with the Git commit IDs they are attached
-to. We can see that the experiment we run has a name `exp-6dccf` and run from
-the commit ID `7317bc6`.
+to. We can see that the experiment we run has a name `exp-6dccf` and was run
+from the commit ID `7317bc6`.
 
 <details>
 
@@ -213,7 +213,7 @@ $ dvc exp show --no-timestamp \
 └─────────────────────────┴────────┴──────────────────┘
 ```
 
-After selecting an experiment from the table you can create a Git branch that
+After selecting an experiment from the table, you can create a Git branch that
 contains the experiment with all its related files.
 
 ```dvc