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Reinforcement Learning with TensorFlow

You're reading from Reinforcement Learning with TensorFlow

Product type Book

Published in Apr 2018

Publisher Packt

ISBN-13 9781788835725

Pages 334 pages

Edition 1st Edition

Languages

Concepts

Reinforcement Learning

Author (1):

Sayon Dutta

Table of Contents (21) Chapters

Title Page

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Contributors

Preface

1. Deep Learning – Architectures and Frameworks

2. Training Reinforcement Learning Agents Using OpenAI Gym

3. Markov Decision Process

4. Policy Gradients

5. Q-Learning and Deep Q-Networks

6. Asynchronous Methods

7. Robo Everything – Real Strategy Gaming

8. AlphaGo – Reinforcement Learning at Its Best

9. Reinforcement Learning in Autonomous Driving

10. Financial Portfolio Management

11. Reinforcement Learning in Robotics

12. Deep Reinforcement Learning in Ad Tech

13. Reinforcement Learning in Image Processing

14. Deep Reinforcement Learning in NLP

1. Further topics in Reinforcement Learning

2. Other Books You May Enjoy

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Index

Appendix 1. Further topics in Reinforcement Learning

In this appendix, we will cover an introductory overview of some of the topics which were out of the scope of this book. But we will mention them in brief and end these topics with external links for you to explore further. This book as has already covered most of the advanced topics in deep reinforcement learning theory as well as active research domains.

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Authors (1)

Sayon Dutta

Sayon Dutta is an Artificial Intelligence researcher and developer. A graduate from IIT Kharagpur, he owns the software copyright for Mobile Irrigation Scheduler. At present, he is an AI engineer at Wissen Technology. He co-founded an AI startup Marax AI Inc., focused on AI-powered customer churn prediction. With over 2.5 years of experience in AI, he invests most of his time implementing AI research papers for industrial use cases, and weightlifting.

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