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: Oracle Press
Pages: 480
ISBN: 978-0138062835
Print: 0138062838
Audience: Developers interested in Oracle PL/SQL
Rating: 4
Reviewer: Kay Ewbank

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Author:  Donis Marshall
Publisher: Addison-Wesley
Pages: 400
ISBN: 978-0137889655
Print: 0137889658
Kindle: B0CLL1TGVT
Audience: Programmers wanting to learn Rust
Rating: 3
Reviewer: Mike James
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