# Tutorials

Tutorials teach by doing. Each one walks you through a complete, working example from start to finish. You will see real output at every step.

## Available tutorials

- [**Getting Started**](getting-started.md) — Train a binary classifier on an imbalanced dataset, progressing from vanilla BCE to Smooth-AP with warmup. By the end you will have a working training loop and a visible improvement in AUCPR.

## What you need

- Python 3.10+
- PyTorch ≥ 2.8
- scikit-learn (for the demo data)

Install everything:

```bash
pip install "imbalanced-losses[demo]"
```
