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Applied Reinforcement Learning with Python

With OpenAI Gym, Tensorflow, and Keras

  • Taweh Beysolow II

Table of contents

  1. Front Matter
    Pages i-xv
  2. Taweh Beysolow II
    Pages 1-17
  3. Taweh Beysolow II
    Pages 19-53
  4. Taweh Beysolow II
    Pages 77-94
  5. Taweh Beysolow II
    Pages 95-112
  6. Back Matter
    Pages 113-168

About this book

Introduction

Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym.

Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through features of OpenAI Gym, from utilizing standard libraries to creating your own environments, then discover how to frame reinforcement learning problems so you can research, develop, and deploy RL-based solutions.


What You'll Learn:

  • Implement reinforcement learning with Python 
  • Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras
  • Deploy and train reinforcement learning–based solutions via cloud resources
  • Apply practical applications of reinforcement learning

Keywords

Reinforcement Learning Python Machine Learning Deep Learning Artificial Intelligence Open AI Gym PyTorch TensorFlow Keras

Authors and affiliations

  • Taweh Beysolow II
    • 1
  1. 1.San FranciscoUSA

Bibliographic information

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