LEARNING · AURÉLIEN GÉRON ON GITHUB
Free
The book author's free notebook repository pairs the current edition with runnable Scikit-Learn, Keras and TensorFlow examples.
This is the companion repository maintained by Aurélien Géron for the third edition of Hands-On Machine Learning. Its notebooks cover practical machine learning and deep learning workflows using Scikit-Learn, Keras and TensorFlow. The repository is public and can be used alongside the physical or ebook chapters.
The best use for Destiny is a chapter-by-chapter loop: read the concept, run the notebook, close it and reproduce the central model or evaluation step from memory, then record one question for a quiz. This turns passive reading into interview-ready explanation and gives you working artifacts to revisit while preparing for AI engineering roles.
The repo is free, but notebook compute is your responsibility. Some chapters may require substantial runtime or memory; Google Colab and Kaggle notebooks provide browser-based execution with free tiers, though availability and quotas can change. Save your own copy and outputs because hosted runtimes are temporary. Avoid spending time polishing notebooks before the concepts and exercises are understood.