Machine Learning with PyTorch and Scikit-Learn

ebook Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili, Dmytro Dzhulgakov
★★★★☆
(4.4) 108 ratings • 12 reviews

Added on January 12, 2026

Description

Key Features

  • Learn applied machine learning with a solid foundation in theory
  • Clear, intuitive explanations take you deep into the theory and practice of Python machine learning
  • Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices

Who this book is for

If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch.

Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.