Advanced Deep Learning with Keras (Packt)
Monday, 24 December 2018

This is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, author Rowel Atienza shows hands-on projects demonstrating how to create more effective AI with the latest techniques. The book includes descriptions of GANs, Variational Autoencoders, and Deep Reinforcement Learning.

<ASIN:1788629418>

 

Author: Rowel Atienza
Publisher: Packt Publishing
Date: October 2018
Pages: 368
ISBN: 978-1788629416
Print: 1788629418
Kindle: B078N8RDCP
Audience: Developers using Keras
Level: Intermediate
Category: Artificial Intelligence

 

Contents include

  • Cutting-edge techniques in human-like AI performance
  • Implement advanced deep learning models using Keras
  • The building blocks for advanced techniques - MLPs, CNNs, and RNNs
  • Deep neural networks – ResNet and DenseNet
  • Autoencoders and Variational AutoEncoders (VAEs)
  • Generative Adversarial Networks (GANs) and creative AI techniques
  • Disentangled Representation GANs, and Cross-Domain GANs
  • Deep Reinforcement Learning (DRL) methods and implementation
  • Produce industry-standard applications using OpenAI gym
  • Deep Q-Learning and Policy Gradient Methods

 

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Publisher: Que
Pages: 352
ISBN: 978-0789751980
Print: 0789751984
Kindle: B00EANJ09U
Audience: Complete beginners
Rating: 4.5
Reviewer: Mike James

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Author: Michael Bolin
Publisher: O'Reilly, 2010
Pages: 592
ISBN: 978-1449381875
Print: 1449381871
Kindle: B0046RERYI
Audience: Existing and potential users of Closure
Rating: 4
Reviewed by: Mike James 


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