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

This book offers a practical, hands-on exploration of deep learning. Author François 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.

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

Author: François 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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100 Go Mistakes and How to Avoid Them

Author: Teiva Harsanyi
Publisher: Manning
Date: October 2022
Pages: 384
ISBN: 978-1617299599
Print: 1617299596
Kindle: B0BBHQD8BQ
Audience: Go Developers
Rating: 3
Reviewer: Mike James
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Continuous Architecture In Practice (Addison-Wesley)

Author: Murat Erder, Pierre Pureur and Eoin Woods
Publisher: Addison-Wesley
Pages: 352
ISBN: 978-0136523567
Print: 0136523560
Kindle: ‎B08ZRTQGLJ
Audience: Software Architects
Rating: 3
Reviewer: Kay Ewbank

This book sets out the case for why software architecture is more important than ever, and in p [ ... ]


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