# Phase 2: ML Fundamentals

> Classical machine learning is still the backbone of most production AI.

## Start this phase on GitHub

**Prerequisites:** Phase 1 Math Foundations and NumPy. Check the route with
`python3 phases/00-setup-and-tooling/01-dev-environment/code/verify.py --route ml-foundations`.

**First lesson:** [What Is Machine Learning](01-what-is-machine-learning/)

Run this command from the repository root:

```bash
python3 phases/02-ml-fundamentals/01-what-is-machine-learning/code/ml_intro.py
```

Keep the command, exit code, test accuracy, random baseline, and one sentence
explaining why the learned classifier beats that baseline.

**Next action:** Change the class separation, predict how accuracy will move,
run it again, then continue to [Linear Regression from Scratch](02-linear-regression/).

Browse the [full Phase 2 lesson list](../../README.md#phase-2) or the
[cross-phase roadmap](../../ROADMAP.md).