Deep Learning books

manning.com / catalog / Data Science / Deep Learning
Vladimir Bok , 2025
Luca Antiga, Eli Stevens, Howard Huang, Thomas Viehmann , 2025
Guglielmo Iozzia , 2025
Numa Dhamani and Maggie Engler , 2025
François Chollet, Tomasz Kalinowski , 2025
Abhinav Kimothi , 2025
(1)
Chrissy LeMaire and Brandon Abshire
Foreword by Nitya Narasimhan
, 2025
François Chollet and Matthew Watson , 2025
Tyler Suard , 2025
Hamza Farooq , 2025
Christopher Kardell and Mark Brouwer , 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
Angelica Lo Duca , 2024
Paul McFedries , 2024
(1)
David Clinton , 2024
(8)
Krishnendu Chaudhury
with Ananya H. Ashok, Sujay Narumanchi, Devashish Shankar
Foreword by Prith Banerjee
, 2024
(1)
Chi Wang and Donald Szeto
Foreword by Silvio Savarese and Caiming Xiong
, 2023
(4)
François Chollet with Tomasz Kalinowski and J. J. Allaire , 2022
Meta Brains , 2022
(1)
Thushan Ganegedara , 2022
(1)
Edward Raff
Foreword by Kirk Borne
, 2022
(86)
François Chollet , 2021
(3)
Andrew Ferlitsch , 2021
Rajeev Ratan , 2021
(1)
Mark Ryan , 2020
(10)
Miguel Morales
Foreword by Charles Isbell
, 2020
Oliver Dürr, Beate Sick, Elvis Murina , 2020
(16)
Eli Stevens, Luca Antiga, and Thomas Viehmann
Foreword by Soumith Chintala
, 2020
(3)
Alexander Zai and Brandon Brown , 2020
(1)
Shanqing Cai, Stanley Bileschi, Eric D. Nielsen with Francois Chollet
Foreword by Nikhil Thorat and Daniel Smilkov
, 2020
(3)
Jakub Langr and Vladimir Bok , 2019
(4)
Grant Sanderson , 2019
Frank Kane , 2019
(2)
Rick J. Scavetta , 2019
(1)
Tommaso Teofili
Foreword by Chris Mattmann
, 2019
(3)
Beau Carnes , 2019
1 2
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