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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
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
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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

Questions

The question list is as follows:

  1. Why and how do we create a new environment in Anaconda?
  2. What is the need for using Docker?
  3. How do we simulate an environment in OpenAI Gym?
  4. How do we check all available environments in OpenAI Gym?
  5. Are OpenAI Gym and Universe the same? If not, what is the reason?
  6. How are TensorFlow variables and placeholders different from each other?
  7. What is a computational graph?
  8. Why do we need sessions in TensorFlow?
  9. What is the purpose of TensorBoard and how do we start it?
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Hands-On Reinforcement Learning with Python
Published in: Jun 2018
Publisher: Packt
ISBN-13: 9781788836524
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Authors (1)

Profile icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more
See other products by Sudharsan Ravichandiran

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