A list of deep learning books:
- Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville
- Grokking Deep Learning by Andrew W. Trask
- Machine Learning Yearning by Andrew Ng
- Neural Networks and Deep Learning by Michael Nielsen
- Deep Learning with Python by Francois Chollet
Deep Learning: An MIT Press book
Authors: Ian Goodfellow and Yoshua Bengio and Aaron Courville.
This book is considered to the “Bible” of Deep Learning and recommended by a lot of people. “It is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.”
We could get the online of the book including its lectures, exercises and other resources.
Grokking Deep Learning
Author: Andrew W. Trask.
This book “teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks.” “For readers with high school-level math and intermediate programming skills.”
Machine Learning Yearning
Author: Andrew Ng
This book “teaches you how to structure Machine Learning projects.” It “is focused not on teaching you ML algorithms, but on how to make ML algorithms work.”
Neural Networks and Deep Learning
Author: Michael Nielsen.
This book teaches neural networks and deep learning.
Deep Learning with Python
Author: Francois Chollet.
This book “_introduces the field of deep learning using the Python language and the powerful Keras library. _”
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