You're reading from TensorFlow 2 Reinforcement Learning Cookbook Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

Product type Paperback

Published in Jan 2021

Publisher Packt

ISBN-13 9781838982546

Length 472 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Reinforcement Learning

Author (1):

Palanisamy

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Table of Contents (11) Chapters

Preface

1. Chapter 1: Developing Building Blocks for Deep Reinforcement Learning Using Tensorflow 2.x

2. Chapter 2: Implementing Value-Based, Policy-Based, and Actor-Critic Deep RL Algorithms FREE CHAPTER

3. Chapter 3: Implementing Advanced RL Algorithms

4. Chapter 4: Reinforcement Learning in the Real World – Building Cryptocurrency Trading Agents

5. Chapter 5: Reinforcement Learning in the Real World – Building Stock/Share Trading Agents

6. Chapter 6: Reinforcement Learning in the Real World – Building Intelligent Agents to Complete Your To-Dos

7. Chapter 7: Deploying Deep RL Agents to the Cloud

8. Chapter 8: Distributed Training for Accelerated Development of Deep RL Agents

9. Chapter 9: Deploying Deep RL Agents on Multiple Platforms

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To get the most out of this book

The code in this book is extensively tested on Ubuntu 18.04 and Ubuntu 20.04 and should work with later versions of Ubuntu if Python 3.6+ is available. With Python 3.6+ installed along with the necessary Python packages, as listed at the start of each of the recipes, the code should run fine on Windows and macOS X too.

It is advised to create and use a Python virtual environment named tfrl-cookbook to install the packages and run the code in this book. A Miniconda or Anaconda installation for Python virtual environment management is recommended.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

It is highly recommended to star and fork the GitHub repository to receive updates and improvements to the code recipes.We urge you to share what you build and also engage with other readers and the community at https://github.com/PacktPublishing/Tensorflow-2-Reinforcement-Learning-Cookbook/discussions.