Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python

by Abhishek Nandy, Manisha Biswas

Master reinforcement learning, a popular area of machine learning, starting with the discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI  before looking at Open AI Gym. You’ll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There’s also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google’s Deep Mind and see scenarios where reinforcement learning can be used. What You'll Learn Absorb the core concepts of the reinforcement learning processUse advanced topics of deep learning and AIWork with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using PythonWho This Book Is ForData scientists, machine learning and deep learning professionals, developers who want to adapt and learn reinforcement learning.

240 pages, Kindle Edition

Published December 7, 2017

Reviews

[Alberto · Rating 1 out of 5]

The book consists entirely of copy & paste of huge chunks of code, with no explanation, and screen shots. It appears to have been an attempt to get up to a (pathetic) total of 163 pages, without actually having to do any writing that would expose the fact that the authors don't know anything about RL that you couldn't learn by reading wikipedia for 10 minutes.

[Mohammadreza Seifollahi · Rating 1 out of 5]

Mostly copy-pasted codes from github and the rest is screenshots for library installation processes.