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rasbt/python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
The companion code repository for Raschka and Mirjalili's Python Machine Learning book (3rd edition, 2019). It covers the full ML stack from scikit-learn basics through CNNs, RNNs, and GANs in TensorFlow 2.x, with one Jupyter notebook per chapter. Aimed at developers who bought the book and want runnable examples alongside the theory.
The chapter-by-chapter structure maps exactly to the book, so you can run code while reading without hunting for which file corresponds to which section. Chapter 12 implements a neural net from scratch in pure NumPy before TensorFlow appears — that's a pedagogically honest choice that most courses skip. The notebooks include both .ipynb and exported .py scripts, which makes diffing and version control actually workable. Coverage is broad without being shallow: clustering, dimensionality reduction, ensemble methods, and deployment (Flask in ch09) all get real treatment.
Last pushed April 2023, and the TensorFlow chapters were written for TF 2.x circa 2019 — the Keras API has shifted enough that several chapters will throw deprecation warnings or outright break on current installs. No requirements.txt or pinned environment file anywhere visible, so reproducing the exact working state is trial and error. The deep learning chapters (13–17) use TF/Keras exclusively with no PyTorch alternative, which is increasingly the wrong bet for anyone doing serious work in 2024+. The repo is dead upstream — issues are open, PRs are stale, and there's no sign of a 4th edition refresh.