Hands-On Machine Learning with Scikit-Learn and PyTorch – Aurélien Géron (Paperback)

Hands-On Machine Learning with Scikit-Learn and PyTorch by Aurélien Géron is the first-edition O’Reilly paperback that teaches machine learning and deep learning by building real projects, from linear regression in Scikit-Learn to transformers, diffusion models and LLM fine-tuning in PyTorch.

Géron’s earlier Hands-On Machine Learning books became the standard practical introduction to the field. This edition moves the deep learning half from TensorFlow and Keras to PyTorch and the Hugging Face ecosystem, which is where most current research and industry code lives. It keeps the same structure: an end-to-end project early, then classification, training models, SVMs, trees and ensembles, dimensionality reduction and unsupervised learning, followed by neural networks, computer vision, sequence models, transformers, generative models and reinforcement learning.

What's included

• Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems, 1st Edition
• Author: Aurélien Géron
• Paperback, published by O’Reilly Media
• ISBN-13 9798341607989
• Covers overfitting, hyperparameter tuning, clustering, anomaly detection, transformers, diffusion models, pretrained LLMs and RL agents
• Code examples in Python with Scikit-Learn, PyTorch and Hugging Face

Who it's for

Software developers moving into machine learning, data analysts who want to go beyond notebooks, computer science students in an applied ML course, and professionals who learned the TensorFlow edition and need to retool for PyTorch and modern LLM workflows.

Why this edition

This is the PyTorch edition, not a reprint of the TensorFlow book. If your team, course or target employer uses PyTorch and Hugging Face, this is the matching text. The project-first approach means you have a working pipeline by chapter two and understand why each later technique exists. It is long, but it is meant to be worked through, not read.

Frequently asked questions

How is this different from Géron’s TensorFlow edition?

The deep learning chapters are rewritten for PyTorch and Hugging Face, with new material on transformers, diffusion models, LLM fine-tuning and agents. The Scikit-Learn foundations are updated too.

Do I need prior machine learning experience?

No. You need comfortable Python and basic math. The book starts from fundamentals.

Is the code available online?

Yes. O’Reilly and the author provide the notebooks on GitHub; the book tells you where.

Details