|Machine Learning with PyTorch and Scikit-Learn (Packt)|
|Friday, 04 March 2022|
This book sets out to be a comprehensive guide to machine learning and deep learning with PyTorch, and to act as both a step-by-step tutorial and a reference. Sebastian Raschka and Yuxi (Hayden) Liu provide explanations, visualizations, and examples, to cover the essential machine learning techniques in depth. This new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).
The book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. It also covers generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning.
Author: Sebastian Raschka , Yuxi (Hayden) Liu
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