Deep Learning with PyTorch, Second Edition

• This book is an exceptional resource for anyone looking to dive into deep learning with the PyTorch framework. It masterfully introduces complex concepts in a way that is approachable for beginners and students, offering clear explanations and practical examples that make learning both engaging and effective.

Raja Rao Budaraju, Senior Member of Technical Staff, Oracle

• If you’re looking for a way to quickly get up to speed in deep learning using PyTorch, I’d highly recommend this book. It’ll provide you with a really solid base to expand and experiment with many different projects using PyTorch.

Jordan Samek, Data Analyst | Data Scientist

Luca Antiga

Luca Antiga is a deep learning researcher and entrepreneur known for translating theory into high-impact AI applications. With extensive industry and academic collaborations, Luca brings clarity and pragmatic rigor to every page. He distills years of neural-network innovation into guidance that accelerates reader competence.

Eli Stevens

Eli Stevens is a seasoned machine-learning engineer recognized for simplifying complex architectures for production teams. With startup intensity and open-source spirit, Eli delivers frank, actionable insights throughout the book. He converts frontier research into approachable steps that help readers deploy real-world solutions.

Howard Huang

Howard Huang is a software engineer on the core PyTorch team, known for advancing distributed training at scale. With insider knowledge of the framework, Howard injects authoritative best practices into the narrative. He turns deep infrastructure expertise into clear tactics that boost reader productivity.

Thomas Viehmann

Thomas Viehmann is a data-science consultant and educator praised for demystifying advanced AI concepts. With classroom experience and community mentorship, Thomas offers an encouraging, structured teaching style. He translates academic depth into tools and patterns readers can apply immediately.