AI Book Club: Hands-On Machine Learning with Scikit-Learn and PyTorch
January's book is "Hands-On Machine Learning with Scikit-Learn and PyTorch"!
This is a casual-style event. Not a structured presentation on topics. Sometimes, the discussion even drifts away from the chapters, but feel free to grab the mic to help steer it back.
Feel free to join the discussion even if you have not read the book chapters! :)
Want to discuss the contents during the reading week? Join the Slack Flyte MLOps Slack group and search for the "ai-reading-club" channel. https://slack.flyte.org/
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About the book:
Title: Hands-On Machine Learning with Scikit-Learn and PyTorch
Authors: Aurélien Géron
Published: October 2025
https://learning.oreilly.com/library/view/hands-on-machine-learning/9798341607972/
Chapters:
1. The Machine Learning Landscape
2. End-to-End Machine Learning Project
3. Classification
4. Training Models
5. Decision Trees
6. Ensemble Learning and Random Forests
7. Dimensionality Reduction
8. Unsupervised Learning Techniques
II. Neural Networks and Deep Learning
9. Introduction to Artificial Neural Networks
10. Building Neural Networks with PyTorch
11. Training Deep Neural Networks
12. Deep Computer Vision Using Convolutional Neural Networks
13. Processing Sequences Using RNNs and CNNs
14. Natural Language Processing with RNNs and Attention
15. Transformers for Natural Language Processing and Chatbots
16. Vision and Multimodal Transformers
17. Speeding Up Transformers
18. Autoencoders, GANs, and Diffusion Models
19. Reinforcement Learning
A. Autodiff
B. Mixed Precision and Quantization
Book Description
The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Whether you're looking to enhance your skill set and apply machine learning to real-world projects or are simply curious about how AI systems function, this book is your jumping-off place.
With an approachable yet deeply informative style, author Aurélien Géron delivers the ultimate introductory guide to machine learning and deep learning. Drawing on the Hugging Face ecosystem, with a focus on clear explanations and real-world examples, the book takes you through cutting-edge tools like Scikit-Learn and PyTorch—from basic regression techniques to advanced neural networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to build intelligent systems.
Understand ML basics, including concepts like overfitting and hyperparameter tuning
Complete an end-to-end ML project using scikit-Learn, covering everything from data exploration to model evaluation
Learn techniques for unsupervised learning, such as clustering and anomaly detection
Build advanced architectures like transformers and diffusion models with PyTorch
Harness the power of pretrained models—including LLMs—and learn to fine-tune them
Train autonomous agents using reinforcement learning
https://learning.oreilly.com/library/view/hands-on-machine-learning/9798341607972/