Deep Learning books

manning.com / catalog / Data Science / Deep Learning
(1)
Chrissy LeMaire and Brandon Abshire
Foreword by Nitya Narasimhan
, 2025
Abhinav Kimothi , 2025
Christopher Kardell and Mark Brouwer , 2025
Luca Antiga, Eli Stevens, Howard Huang, Thomas Viehmann , 2025
(13)
Sebastian Raschka , 2024
(8)
Numa Dhamani and Maggie Engler
Foreword by Sahar Massachi
, 2024
(2)
Mark Liu
Foreword by Sarah Sanders
, 2024
(1)
Artur Guja, Marlena Siwiak, and Marian Siwiak
Foreword by Sue Tripathi
, 2024
Grigory Sapunov , 2024
Paul McFedries , 2024
(1)
David Clinton , 2024
Michael Yuan and Tony Yuan , 2024
(8)
Krishnendu Chaudhury
with Ananya H. Ashok, Sujay Narumanchi, Devashish Shankar
Foreword by Prith Banerjee
, 2024
Pablo Elgueta , 2024
Anuradha Kar , 2024
Anuradha Kar , 2024
Anuradha Kar , 2024
Anuradha Kar , 2024
Anuradha Kar , 2024
Martine Dowden , 2024
Rod Stephens , 2024
Rod Stephens , 2024
Rod Stephens , 2024
(1)
Chi Wang and Donald Szeto
Foreword by Silvio Savarese and Caiming Xiong
, 2023
Mark Ryan , 2021
Kanishka Tyagi & Raghavendra Sriram , 2022
Kanishka Tyagi & Raghavendra Sriram , 2022
(4)
François Chollet with Tomasz Kalinowski and J. J. Allaire , 2022
Meta Brains , 2022
Delio D'Anna , 2022
(1)
Thushan Ganegedara , 2022
Ferhat Özgur Catak , 2022
Ferhat Özgur Catak , 2022
(1)
Edward Raff
Foreword by Kirk Borne
, 2022
Xiaotian Han , 2021
Xiaotian Han , 2021
Xiaotian Han , 2021
Xiaotian Han , 2021
(86)
François Chollet , 2021
(3)
Andrew Ferlitsch , 2021
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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