handson-ml3 contains the Jupyter notebooks and code for the third edition of the book Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow. It guides readers through modern machine learning and deep learning workflows using Python, with examples spanning data preparation, supervised and unsupervised learning, deep neural networks, RL, and production-ready model deployment. The third edition updates the content for TensorFlow 2 and Keras, introduces new chapters (for example on reinforcement learning or generative models), and offers best-practice code that reflects current ecosystems. The notebooks are designed so you can run them locally or on Colab/online, making it accessible for learners regardless of infrastructure. The author includes solutions for exercises and sets up an environment specification so you can reproduce results. Because the discipline of ML evolves rapidly, this repo serves both as a learning path and a reference library you can revisit as models.
Features
- Complete Jupyter notebooks aligned to the third-edition book chapters
- Up-to-date code using Scikit-Learn, Keras and TensorFlow 2
- Reproducible environment setup (environment.yml, instructions)
- Coverage of both classical ML and modern deep learning topics
- Exercise solutions included to aid self-study or teaching
- Ready for Colab or local execution to lower setup friction