ageron/handson-ml

Jupyter notebooks covering supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), and neural networks using scikit-learn and TensorFlow 1.x. The materials progress from foundational concepts through practical implementations, with embedded exercises and real-world datasets like the California housing dataset. Supports execution across multiple platforms via Colaboratory, Binder, Docker, or local Anaconda environments.

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