Deep Reinforcement Learning with Python: Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, 2nd Edition

Author:   Sudharsan Ravichandiran
Publisher:   Packt Publishing Limited
Edition:   2nd Revised edition
ISBN:  

9781839210686


Pages:   760
Publication Date:   30 September 2020
Format:   Paperback
Availability:   Available To Order   Availability explained
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Deep Reinforcement Learning with Python: Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow, 2nd Edition


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Author:   Sudharsan Ravichandiran
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
Edition:   2nd Revised edition
ISBN:  

9781839210686


ISBN 10:   1839210680
Pages:   760
Publication Date:   30 September 2020
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Table of Contents Fundamentals of Reinforcement Learning A Guide to the Gym Toolkit The Bellman Equation and Dynamic Programming Monte Carlo Methods Understanding Temporal Difference Learning Case Study - The MAB Problem Deep Learning Foundations A Primer on TensorFlow Deep Q Network and Its Variants Policy Gradient Method Actor-Critic Methods - A2C and A3C Learning DDPG, TD3, and SAC TRPO, PPO, and ACKTR Methods Distributional Reinforcement Learning Imitation Learning and Inverse RL Deep Reinforcement Learning with Stable Baselines Reinforcement Learning Frontiers Appendix 1 - Reinforcement Learning Algorithms Appendix 2 - Assessments

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Author Information

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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