Deep Learning books

manning.com / catalog / Data Science / Deep Learning
(4)
Howard Huang, Eli Stevens, Luca Antiga, Thomas Viehmann , 2026
Ben Auffarth , 2026
Pere Martra , 2026
(9)
Sebastian Raschka , 2026
(1)
Quan Nguyen , 2026
Satyajit Pattnaik , 2026
Satyajit Pattnaik , 2026
Satyajit Pattnaik , 2026
Satyajit Pattnaik , 2026
Tomasz Lelek and Artur Skowroński , 2026
Elliot Arledge , 2026
Jeremie Charlet , 2026
Jeremie Charlet , 2026
Jeremie Charlet , 2026
Jeremie Charlet , 2026
(1)
Jungjun Hur and Younghee Song , 2026
(1)
Micheal Lanham , 2026
Tobias Zwingmann , 2026
Tobias Zwingmann , 2026
Tobias Zwingmann , 2026
Tobias Zwingmann , 2026
(3)
Richard Heimann , 2026
(2)
Hamza Farooq , 2026
(1)
Rishal Hurbans , 2026
Raj Abhijit Dandekar, Rajat Dandekar, Sreedath Panat, Naman Dwivedi , 2025
Numa Dhamani and Maggie Engler
Foreword by Alice Hunsberger
, 2025
Val Andrei Fajardo , 2025
Luis G. Serrano , 2025
(1)
Mark Liu , 2025
(3)
Guglielmo Iozzia , 2025
(1)
Engin Bozdag and Stefano Bennati , 2025
(1)
Hadi Aghazadeh , 2025
(16)
François Chollet and Matthew Watson , 2025
(2)
Tyler Suard , 2025
(1)
François Chollet, Tomasz Kalinowski , 2025
(1)
Christopher Kardell and Mark Brouwer , 2025
(2)
Keita Broadwater and Namid Stillman
Foreword by Matthias Fey
, 2025
(72)
Sebastian Raschka , 2024
(3)
Mark Liu
Foreword by Sarah Sanders
, 2024
Angelica Lo Duca , 2024
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Dive into the transformative world of deep learning, where artificial neural networks push the boundaries of what's possible in AI. From fundamental concepts to advanced architectures, discover comprehensive resources on training neural networks, computer vision, natural language processing, and generative AI. Learn practical implementations using popular frameworks like PyTorch, TensorFlow, and JAX, while mastering essential techniques in model deployment, optimization, and scalability. Whether you're interested in building custom language models, implementing computer vision solutions, or exploring cutting-edge applications in financial technology, our collection covers both theoretical foundations and hands-on applications. Perfect for beginners and experienced practitioners alike, these resources will help you navigate the complex landscape of modern deep learning and its real-world applications. For a more detailed breakdown, take a look at the following categories: Generative AI books