Deep Learning with PyTorch, Second Edition

"Deep Learning with PyTorch, Second Edition" is a comprehensive guide for Python programmers interested in building neural networks and generative AI models using the latest version of the PyTorch library. Updated by core PyTorch developer Howard Huang, the book covers fundamental deep learning techniques, mastering PyTorch’s flexible APIs, and implementing advanced models such as CNNs, transformers, and diffusion models through practical, hands-on projects. It also focuses on optimizing models for training and deployment, providing essential tools and techniques for creating efficient machine learning systems in real-world applications.