# Optimization

Optimization guides highlight practical solvers for tuning models and experiments. Compare gradient-free Nevergrad strategies with SciPy-based routines and learn when to apply each.

```{toctree}
:maxdepth: 1

01_nevergrad_optimizer.ipynb
02_scipy_optimizer.ipynb
03_optax_getting_started.ipynb
04_learning_rate_scheduling.ipynb
05_advanced_optimizers.ipynb
```