Deep Learning With Python (Manning)
Deep Learning With Python (Manning)
Thursday, 28 December 2017

This book offers a practical, hands-on exploration of deep learning. Author Fran├žois Chollet, the creator of Keras and a Google AI researcher, avoids mathematical notation, preferring instead to explain quantitative concepts via code snippets and to build practical intuition about the core ideas of machine learning and deep learning. More than 30 code examples include detailed commentary, practical recommendations, and simple high-level explanations of everything you need to know to start using deep learning to solve concrete problems.

<ASIN:1617294438>

The code examples use the Python deep-learning framework Keras, with TensorFlow as a backend engine.

Author: Fran├žois Chollet
Publisher: Manning
Date: Nov 2017
Pages: 384
ISBN: 978-1617294433
Print: 1617294438
Kindle: free with print book
Audience: AI developers
Level: intermediate
Category: Artificial Intelligence

 

deeppython

 

Contents include:

  • The mathematical building blocks of neural networks
  • Fundamentals of machine learning
  • Deep learning for computer vision
  • Deep learning for text and sequences
  • Advanced deep learning best practices
  • Generative deep learning

 

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C Primer Plus, 6e

Author: Stephen Prata
Publisher: Addison Wesley
Pages: 1080
ISBN: 978-0321928429
Print: 0321928423
Kindle: B00GWLPX76
Audience: Beginners
Rating: 4
Reviewer: Mike James

C is still a language worth learning and knowing about. 



JavaScript Cookbook (2nd Ed)

Author: Shelley Powers
Publisher: O'Reilly, 2015
Pages: 634
ISBN: 978-1491901885
Print: 1491901888
Kindle: B00SS9G9DC
Audience: Intermediate JavaScript programmers
Rating: 4.5
Reviewed by: Ian Elliot 

A cookbook for the more advanced programmer? Is this a good idea?


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