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Deep Reinforcement Learning Hands-On. - Second Edition

You're reading from  Deep Reinforcement Learning Hands-On. - Second Edition

Product type Book
Published in Jan 2020
Publisher Packt
ISBN-13 9781838826994
Pages 826 pages
Edition 2nd Edition
Languages
Concepts
Author (1):
Maxim Lapan Maxim Lapan
Profile icon Maxim Lapan
LinkedIn
Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
See other products by Maxim Lapan

Table of Contents (28) Chapters

Preface What Is Reinforcement Learning? OpenAI Gym Deep Learning with PyTorch The Cross-Entropy Method Tabular Learning and the Bellman Equation Deep Q-Networks Higher-Level RL Libraries DQN Extensions Ways to Speed up RL Stocks Trading Using RL Policy Gradients – an Alternative The Actor-Critic Method Asynchronous Advantage Actor-Critic Training Chatbots with RL The TextWorld Environment Web Navigation Continuous Action Space RL in Robotics Trust Regions – PPO, TRPO, ACKTR, and SAC Black-Box Optimization in RL Advanced Exploration Beyond Model-Free – Imagination AlphaGo Zero RL in Discrete Optimization Multi-agent RL Other Books You May Enjoy
Index

Who this book is for

The main target audience is people who have some knowledge of ML, but want to get a practical understanding of the RL domain. The reader should be familiar with Python and the basics of DL and ML. An understanding of statistics and probability is an advantage, but is not absolutely essential for understanding most of the book’s material.

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Authors (1)

Profile icon Maxim Lapan
LinkedIn
Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
See other products by Maxim Lapan

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