Book Image

Python Reinforcement Learning Projects

By : Sean Saito, Yang Wenzhuo, Rajalingappaa Shanmugamani
Book Image

Python Reinforcement Learning Projects

By: Sean Saito, Yang Wenzhuo, Rajalingappaa Shanmugamani

Overview of this book

Reinforcement learning is one of the most exciting and rapidly growing fields in machine learning. This is due to the many novel algorithms developed and incredible results published in recent years. In this book, you will learn about the core concepts of RL including Q-learning, policy gradients, Monte Carlo processes, and several deep reinforcement learning algorithms. As you make your way through the book, you'll work on projects with datasets of various modalities including image, text, and video. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore technologies such as TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and even build other neural networks. By the end of this book, you will have hands-on experience with eight reinforcement learning projects, each addressing different topics and/or algorithms. We hope these practical exercises will provide you with better intuition and insight about the field of reinforcement learning and how to apply its algorithms to various problems in real life.

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Table of Contents (17 chapters)
Title Page
Title Page
Copyright and Credits
Copyright and Credits
Packt Upsell
Packt Upsell
Contributors
Contributors
Preface
Preface
Free Chapter
1
Up and Running with Reinforcement Learning
Up and Running with Reinforcement Learning
Introduction to this book
What is reinforcement learning?
Deep learning
Summary
References
2
Balancing CartPole
Balancing CartPole
OpenAI Gym
Markov models
Summary
3
Playing Atari Games
Playing Atari Games
Introduction to Atari games
Building an Atari emulator
Data preparation
Deep Q-learning
Implementation of DQN
Experiments
Summary
4
Simulating Control Tasks
Simulating Control Tasks
Introduction to control tasks
Deterministic policy gradient
Trust region policy optimization
Summary
5
Building Virtual Worlds in Minecraft
Building Virtual Worlds in Minecraft
Introduction to the Minecraft environment
Data preparation
Asynchronous advantage actor-critic algorithm
Implementation of A3C
Experiments
Summary
6
Learning to Play Go
Learning to Play Go
A brief introduction to Go
Monte Carlo tree search
AlphaGo
AlphaGo Zero
Implementing AlphaGo Zero
Summary
References
7
Creating a Chatbot
Creating a Chatbot
The background problem
Step-by-step guide
Summary
8
Generating a Deep Learning Image Classifier
Generating a Deep Learning Image Classifier
Neural Architecture Search
Implementing NAS
Advantages of NAS
Summary
9
Predicting Future Stock Prices
Predicting Future Stock Prices
Background problem
Data used
Step-by-step guide
Summary
10
Looking Ahead
Looking Ahead
The shortcomings of reinforcement learning
Upcoming developments in reinforcement learning
Summary
References
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think
Index
Index

Copyright and Credits

Python Reinforcement Learning Projects

Copyright © 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Commissioning Editor: Pravin DhandreAcquisition Editor:Divya PoojariContent Development Editor: Snehal KolteTechnical Editor: Dharmendra YadavCopy Editor: Safis EditingProject Coordinator: Manthan PatelProofreader: Safis EditingIndexer:Tejal Daruwale SoniGraphics:Jisha ChirayilProduction Coordinator: Deepika Naik

First published: September 2018

Production reference: 1280918

Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.

ISBN  978-1-78899-161-2

www.packtpub.com

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