ageron/handson-ml3 resource

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14010 stars · 5266 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A series of Jupyter notebooks teaching the fundamentals of Machine Learning and Deep Learning in Python, accompanying the 3rd edition of the O'Reilly book 'Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow'. It includes example code and exercise solutions runnable locally, in Docker, or on Colab/Kaggle/Binder.

Use cases

• learn machine learning fundamentals with scikit-learn
• learn deep learning with tensorflow and keras
• find solutions to hands-on ML book exercises
• run ML tutorials in a Jupyter notebook environment
• get started with neural networks in python

When to choose

• you are learning ML/DL from scratch or following the Hands-on ML book
• you want runnable, well-maintained example notebooks with exercise solutions
• you prefer browser-based environments like Colab or Kaggle

When to avoid

• you need production-ready ML code or a reusable library
• you want a course with videos or graded assignments rather than notebooks
• you need coverage of ML frameworks other than Scikit-Learn, Keras, and TensorFlow

Facets

learning-resource · maturity active

machine-learning deep-learning data-science machine-learning deep-learning data-science tutorials python cross-platform jupyter-notebooks scikit-learn tensorflow keras education book-companion

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