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Hands-On Reinforcement Learning with Python

You're reading from   Hands-On Reinforcement Learning with Python Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788836524
Length 318 pages
Edition 1st Edition
Languages
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Table of Contents (16) Chapters Close

Preface 1. Introduction to Reinforcement Learning 2. Getting Started with OpenAI and TensorFlow FREE CHAPTER 3. The Markov Decision Process and Dynamic Programming 4. Gaming with Monte Carlo Methods 5. Temporal Difference Learning 6. Multi-Armed Bandit Problem 7. Deep Learning Fundamentals 8. Atari Games with Deep Q Network 9. Playing Doom with a Deep Recurrent Q Network 10. The Asynchronous Advantage Actor Critic Network 11. Policy Gradients and Optimization 12. Capstone Project – Car Racing Using DQN 13. Recent Advancements and Next Steps 14. Assessments 15. Other Books You May Enjoy

Setting up your machine

Installing OpenAI is not a straightforward task; there are a set of steps that have to be correctly followed for setting the system up and running it. Now, let's see how to set up our machine and install OpenAI Gym and Universe.

Installing Anaconda

All the examples in the book use the Anaconda version of Python. Anaconda is an open source distribution of Python. It is widely used for scientific computing and processing a large volume of data. It provides an excellent package management environment. It provides support for Windows, macOS, and Linux. Anaconda comes with Python installed along with popular packages used for scientific computing such as NumPy, SciPy, and so on.

To download Anaconda...

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Hands-On Reinforcement Learning with Python
Published in: Jun 2018
Publisher: Packt
ISBN-13: 9781788836524
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