Everything you need to create neural networks with PyTorch, including Large Language and diffusion models. Deep Learning with PyTorch, Second Edition updates the bestselling original guide with new insights into the transformers architecture and generative AI models. Instantly familiar to anyone who knows PyData tools like NumPy and Scikit-learn, PyTorch simplifies Deep Learning without sacrificing advanced features. In Deep Learning with PyTorch, Second Edition you’ll learn how to create your own neural network and Deep Learning systems and take full advantage of PyTorch’s built-in tools for automatic differentiation, hardware acceleration, distributed training, and more. PyTorch makes it easy to build the powerful neural networks that underpin many modern advances in Artificial Intelligence. This second edition has been thoroughly revised by PyTorch core developer Howard Huang to cover the latest features and applications, including generative AI models. The book is written for developers, students, or even hobbyists who have some prior experience with the Python programming language and want to gain a better understanding of Deep Learning.