Revert "guide: undo starting How To subsection"

This reverts commit e6d5f78.

Extracted from #1581 (comment)

content/docs/sidebar.json

@@ -102,7 +102,12 @@
           "katacoda": "https://katacoda.com/dvc/courses/examples/dvcignore"
         }
       },
-      "updating-tracked-files",
+      {
+        "label": "How To",
+        "slug": "how-to",
+        "source": false,
+        "children": ["update-tracked-files"]
+      },
       "setup-google-drive-remote",
       "large-dataset-optimization",
       "external-dependencies",

content/docs/user-guide/how-to/best-practices.md

@@ -0,0 +1,43 @@
+# Best Practices for DVC Projects
+
+Data scientists, engineers, or managers may already know or can easily find
+answers to some of these questions. However, the variety of answers and
+approaches makes data science collaboration a nightmare. **A systematic approach
+is required.**
+
+## Questions on...
+
+### Source code and data versioning
+
+- How do you avoid discrepancies between
+  [revisions](https://git-scm.com/docs/revisions) of source code and versions of
+  data files, when the data cannot fit into a traditional repository?
+
+### Experiment time log
+
+- How do you track which of your
+  [hyperparameter](<https://en.wikipedia.org/wiki/Hyperparameter_(machine_learning)>)
+  changes contributed the most to producing or improving your target
+  [metric](/doc/command-reference/metrics)? How do you monitor the degree of
+  each change?
+
+### Navigating through experiments
+
+- How do you recover a model from last week without wasting time waiting for the
+  model to retrain?
+
+- How do you quickly switch between a large dataset and a small subset without
+  modifying source code?
+
+### Reproducibility
+
+- How do you run a model's evaluation process again without retraining the model
+  and preprocessing a raw dataset?
+
+### Managing and sharing large data files
+
+- How do you share models trained in a GPU environment with colleagues who don't
+  have access to a GPU?
+
+- How do you share the entire 147 GB of your ML project, with all of its data
+  sources, intermediate data files, and models?