Tutorials
=========

This section contains tutorials and examples that demonstrate how to use MLAI for learning machine learning concepts.

.. toctree::
   :maxdepth: 2
   :caption: Tutorials:

   linear_regression
   logistic_regression
   perceptron
   basis_functions
   gp_tutorial
   deepgp_tutorial
   mountain_car

Getting Started
--------------

If you're new to MLAI, we recommend starting with the :doc:`../quickstart` guide before diving into these tutorials.

Each tutorial is designed to be educational and includes:

- Clear explanations of the underlying concepts
- Step-by-step code examples
- Mathematical background where relevant
- Visualizations to aid understanding

Tutorial Structure
-----------------

- *Linear Regression*: Foundation of supervised learning with basis functions
- *Logistic Regression*: Binary classification with probabilistic modeling
- *Perceptron Algorithm*: Simple linear classifier and learning algorithm
- *Basis Functions*: Feature transformation for non-linear modeling
- *Gaussian Process Tutorial*: Introduction to Gaussian Processes
- *Deep GP Tutorial*: Advanced concepts with Deep Gaussian Processes  
- *Mountain Car Example*: Reinforcement learning with the mountain car environment