
&lt;!-- 3. **Assess** its performance. --&gt;
&lt;!-- 4. Repeat steps 1-3 for different models, and choose the **best** model. --&gt;

&lt;!-- -- --&gt;

&lt;!-- .note[Note:] "Different models" can mean: --&gt;

&lt;!-- * Either completely distinct models (e.g., OLS vs. *k*-nearest neighbors). --&gt;
&lt;!-- * Or a set of closely related models differing by a **hyperparameter**. --&gt;
&lt;!--   - E.g., polynomial regression (hyperparameter: polynomial degree). --&gt;


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## How to predict

The basic wor