# Hands-On Machine Learning

Source: https://listme.name/books/hands-on-machine-learning
Website: https://openlibrary.org/works/OL20709638W

Practical machine learning with scikit-learn, Keras and TensorFlow

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is a book by Aurélien Géron, published by O'Reilly Media. Its subtitle is Concepts, Tools, and Techniques to Build Intelligent Systems. The 2022 O'Reilly editions in the Open Library record run to about 850 pages.

The book teaches machine learning in Python with three libraries. Scikit-learn covers classical models, and Keras and TensorFlow cover neural networks, so readers see both kinds of method in code. The subtitle frames it as concepts, tools and techniques for building intelligent systems, and the hands-on method is central to how it teaches.

O'Reilly publishes it in print, and the 2022 editions in the Open Library record run to about 850 pages. It is not free to read online. The book gives less mathematical depth than the theory texts in this list, but it is more practical than most of them, which makes it a useful companion to Deep Learning and Probabilistic Machine Learning.

- Paid | Print
- Price: Print editions from O'Reilly; price varies by seller
- Checked: 2026-10-10

## Strengths

- Teaches methods through code
- Covers scikit-learn, Keras and TensorFlow
- Recent 2022 edition

## Limits

- Less mathematical depth than the theory texts
- No free full text online

## Rankings

- #6 of 13 in [best AI and machine learning books](https://listme.name/best/ai-and-machine-learning-books), score 87.0: Practical code for classical models and neural networks, built on scikit-learn, Keras and TensorFlow. It is paid with no free text, and it goes less deep into theory than the books above it.

## Alternatives

- [Deep Learning](https://listme.name/books/deep-learning-book), score 94.5
- [Probabilistic Machine Learning: An Introduction](https://listme.name/books/probabilistic-machine-learning), score 92.5
- [Dive into Deep Learning](https://listme.name/books/dive-into-deep-learning), score 91.0
- [An Introduction to Statistical Learning (Python edition)](https://listme.name/books/introduction-to-statistical-learning), score 90.0
- [Deep Learning with Python, Third Edition](https://listme.name/books/deep-learning-with-python), score 88.5
- [Mathematics for Machine Learning](https://listme.name/books/mathematics-for-machine-learning), score 85.5
- [Build a Large Language Model (From Scratch)](https://listme.name/books/build-a-large-language-model-from-scratch), score 85.0
- [Pattern Recognition and Machine Learning](https://listme.name/books/pattern-recognition-and-machine-learning), score 84.0