Artificial Intelligence notes

A collection of interactive notes related to Artificial Intelligence.

Dependencies and toolchain

This project is built with the following software:

• the Python programming language;
• Poetry for dependency management and deployment;
• Black for code formatting;
• Pylint to detect programming mistakes before execution;

Additionally, it uses the following tools to create the online version of these notes:

• Jupytext to synchronize Python source files with Jupyter notebooks;
• Jupyter Book to generate a static website from the notebooks;
• A GitHub Action to implement Continuous Integration and publish the website to GitHub Pages after each code push.

When teaching, I run the notebooks in a local Jupyter server and use RISE to showcase them as live reveal.js-based presentations.

Development notes

Once a new .ipynb is created in the docs/ folder, it is automagically paired with a .py file by the same name in the ainotes/ folder. Afterwards, all updates to either file will be reflected into the other. This is configured in the pyproject.toml file.

The .ipynb files are still versioned in order to show their output online, and access them from cloud execution platforms like Google Colaboratory.

Here are some useful commands for running this project:

# Reformat all Python files
black ainotes/

# Check the code for mistakes
pylint ainotes/*

# Force resync of all notebook files (in docs/) with Python files (in ainotes/)
# Add the --execute flag to rerun all notebooks
jupytext --sync ainotes/**/*.py

# Build the website locally from notebook files
# Output is in the docs/_build/ subfolder
jupyter-book build docs/  # Or simply: jb build docs/

# Generate a PDF version of a chapter
# GIF files must be replaced by their static counterparts (PNG or JPG) in the notebook before launching this command
jupyter nbconvert --to PDF {notebook_file_name}