start: Add a parameters hidden section to experiments to merge params/metrics into experiments

content/docs/start/experiments.md

@@ -120,6 +120,32 @@ Experiment results have been applied to your workspace.
 
 <details>
 
+### ℹ️ More information about (Hyper)parameters
+
+It's pretty common for data science projects to include configuration files that
+define adjustable parameters to train a model, adjust model architecture, do
+pre-processing, etc. DVC provides a mechanism for experiments to depend on the
+specific variables from a file.
+
+By default, DVC assumes that a parameters file named `params.yaml` is available
+in your project. DVC parses this file and creates dependencies to the variables
+found in it: `model.conv_units` and `train.epochs`. Example:
+
+```yaml
+train:
+  epochs: 10
+model:
+  conv_units: 16
+```
+
+When you use `dvc exp run --set-param`, DVC updates the parameters in
+`params.yaml` with the values you set in the command line before running the
+experiment.
+
+</details>
+
+<details>
+
 ### ⚙️ Run multiple experiments in parallel
 
 Instead of running the experiments one-by-one, we can define them to run in a