Deep Learning books

manning.com / catalog / Data Science / Deep Learning
(12)
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
(4)
Alexander Zai and Brandon Brown , 2020
(2)
Shanqing Cai, Stanley Bileschi, Eric D. Nielsen with Francois Chollet
Foreword by Nikhil Thorat and Daniel Smilkov
, 2020
(4)
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
Oliver Zeigermann , 2019
(7)
François Chollet , 2017
(8)
Andrew W. Trask , 2019
(1)
Phil Tabor , 2019
(10)
Max Pumperla and Kevin Ferguson
Foreword by Thore Graepel
, 2019
Kesha Williams , 2018
(4)
François Chollet with J. J. Allaire , 2018
Dan Van Boxel , 2017
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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