Generative AI with PyTorch: The Complete Hands-On Guide to GANs, VAEs, Diffusion, and Large Language Models
Generative AI with PyTorch is a complete, hands-on guide for engineers, researchers, and applied practitioners who want to build modern generative systems - from GANs and VAEs to diffusion models and large language models. Packed with clear theory, practical design patterns, and production-ready PyTorch code, this book shows you not only what works, but why - and how to make it work in real projects.
Inside you'll find:
- concise math and intuition for each model family;
- end-to-end PyTorch implementations and debugging recipes;
- practical chapters on training stability, evaluation, scaling, and deployment;
- chapters on multimodal models, audio/speech, and ethical safeguards.
Whether you're prototyping photorealistic image synthesis, building a text generation pipeline, or deploying generative systems at scale, Nicholas Clarke gives you the tools and checklists to move from experiments to reliable products. Hands-on exercises, sample code, and diagnostic workflows make this an ideal reference for self-learners and engineering teams alike.
Buy this book to master modern generative architectures, accelerate experiments with production patterns, and ship responsible AI systems using PyTorch.
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