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index.qmd
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---
format:
html:
toc: false
---
## Welcome
These are the materials for workshops on [tidymodels](https://www.tidymodels.org/) offered at [posit::conf 2024](https://posit.co/conference/). The tidymodels framework is a collection of packages for modeling and machine learning using [tidyverse](https://www.tidyverse.org/) principles. This website hosts the materials for both the _Introduction to tidymodels_ and _Advanced tidymodels_ courses.
_Introduction to tidymodels_ will teach you core tidymodels packages and their uses: data splitting/resampling with rsample, model fitting with parsnip, measuring model performance with yardstick, and model optimization using the tune package. Time permitting, you'll be introduced to basic pre-processing with recipes. You'll learn tidymodels syntax as well as the process of predictive modeling for tabular data.
_Advanced tidymodels_ will teach you about model optimization using the tune and finetune packages, including racing and iterative methods. You'll be able to do more sophisticated feature engineering with recipes. Time permitting, model ensembles via stacking will be introduced. This course is focused on the analysis of tabular data and does not include deep learning methods.
## Is this workshop for me? <img src="slides/images/parsnip-flagger.jpg" align="right" height="150"/>
Depending on your background, one of _Introduction to tidymodels_ or _Advanced tidymodels_ might serve you better than the other.
### Introduction to tidymodels
This workshop is for you if you:
- are comfortable using tidyverse packages to read data into R, transform and reshape data, and make a variety of graphs, and
- have had some exposure to basic statistical concepts such as linear models, residuals, etc.
Intermediate or expert familiarity with modeling or machine learning is not required. Interested students who have intermediate or expert familiarity with modeling or machine learning may be interested in the _Advanced tidymodels_ workshop.
### Advanced tidymodels
This workshop is for you if you:
- have the prerequisite skills listed for the _Introduction to tidymodels_ workshops,
- have used tidymodels packages like recipes, rsample, and parsnip, and
- have some experience with evaluating statistical models using resampling techniques like v-fold cross-validation or the bootstrap.
Participants who are new to tidymodels or machine learning will benefit from taking the _Introduction to tidymodels_ workshop before joining this one. Participants who have completed the "Introduction to tidymodels" workshop will be well-prepared for this course.
## Preparation
The process to set up your computer for either workshop will look the same. Please join the workshop with a computer that has the following installed (all available for free):
- A recent version of R, available at <https://cran.r-project.org/>
- A recent version of RStudio Desktop (RStudio Desktop Open Source License, at least v2024.04.0), available at <https://posit.co/download/rstudio-desktop/>
- For _all of the slides_, the following R packages can be installed from the R console:
```{r}
#| label: installs
#| eval: false
#| echo: true
# Install the packages for the workshop
pkgs <-
c("bonsai", "Cubist", "doParallel", "earth", "embed", "finetune",
"forested", "lightgbm", "lme4", "parallelly", "plumber", "probably",
"ranger", "rpart", "rpart.plot", "rules", "splines2", "stacks",
"text2vec", "textrecipes", "tidymodels", "vetiver")
install.packages(pkgs)
```
**For the advanced course**, you should install the newest version of the dials package (version 1.3.0). To check this, you can run:
```{r}
#| label: check-dials
#| eval: false
#| echo: true
rlang::check_installed("dials", version = "1.3.0")
```
If you're a Windows user and encounter an error message during installation noting a missing Rtools installation, install Rtools using the installer linked [here](https://cran.r-project.org/bin/windows/Rtools/).
## Slides
These slides are designed to use with live teaching and are published for workshop participants' convenience. They are not meant as standalone learning materials. For that, we recommend [tidymodels.org](https://www.tidymodels.org/start/) and [*Tidy Modeling with R*](https://www.tmwr.org/).
### Introduction to tidymodels
- 01: [Introduction](slides/intro-01-introduction.html){target="_blank"}
- 02: [Your data budget](slides/intro-02-data-budget.html){target="_blank"}
- 03: [What makes a model?](slides/intro-03-what-makes-a-model.html){target="_blank"}
- 04: [Evaluating models](slides/intro-04-evaluating-models.html){target="_blank"}
- 05: [Tuning models](slides/intro-05-tuning-models.html){target="_blank"}
- 06: [Wrapping up](slides/intro-06-wrapping-up.html){target="_blank"}
### Advanced tidymodels
- 01: [Introduction](slides/advanced-01-introduction.html){target="_blank"}
- 02: [Feature engineering using recipes](slides/advanced-02-feature-engineering.html){target="_blank"}
- 03: [Tuning hyperparameters (grid search)](slides/advanced-03-tuning-hyperparameters.html){target="_blank"}
- 04: [Grid search via racing](slides/advanced-04-racing.html){target="_blank"}
- 05: [Iterative search](slides/advanced-05-iterative.html){target="_blank"}
- 06: [Wrapping up](slides/advanced-06-wrapping-up.html){target="_blank"}
### Extra content (time permitting)
- [Intro: Using workflowsets](slides/intro-extra-workflowsets.html){target="_blank"}
- [Intro: Using recipes](slides/intro-extra-recipes.html){target="_blank"}
- [Advanced: Transit case study (includes stacking)](slides/extras-transit-case-study.html){target="_blank"}
- [Advanced: Effect encoding](slides/extras-effect-encodings.html){target="_blank"}
- [Advanced: Model deployment](slides/extras-vetiver.html){target="_blank"}
There's also a page for [slide annotations](slides/annotations.html){target="_blank"}; these are extra notes for selected slides.
## Code
Quarto files for working along [are available on GitHub](https://github.com/tidymodels/workshops/tree/main/classwork). (Don't worry if you haven't used Quarto before; it will feel familiar to R Markdown users.)
## Past workshops
### English
- [August 2024](archive/2024-08-posit-conf/index.html) at posit::conf()
- [September 2023](archive/2023-09-posit-conf/) at posit::conf()
- [July 2023](archive/2023-07-nyr/) at the New York R Conference
- [August 2022](archive/2022-08-Reykjavik-City/) in Reykjavik
- [July 2022](archive/2022-07-RStudio-conf/index.html) at [rstudio::conf()](https://posit.co/blog/talks-and-workshops-from-rstudio-conf-2022/)
### Spanish
- [March 2024](archive/2024-03-conectaR-spanish/) at [conectaR](https://congresos.ucr.ac.cr/event/7/)
## Acknowledgments {.appendix}
This website, including the slides, is made with [Quarto](https://quarto.org/). Please [submit an issue](https://github.com/tidymodels/workshops/issues) on the GitHub repo for this workshop if you find something that could be fixed or improved.
## Reuse and licensing {.appendix}
Unless otherwise noted (i.e. not an original creation and reused from another source), these educational materials are licensed under Creative Commons Attribution [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).