Reinforcement Learning With Python: An Introduction (Adaptive Computation and Machine Learning series) PDF [Direct Link]

Reinforcement learning python pdf
Edition2nd edition
Pages88 pages
Format:Pdf
ISBN• ISBN-10: 197436402X
• ISBN-13: 978-1974364022
Book nameReinforcement learning by python
Publisher CreateSpace Independent Publishing Platform; 1 edition (August 12, 2017)
Language English
Author:Stuart Broad (Author)

Introduction:

Reinforcement learning was not that easy before. it has rapid growth with the time. The new algorithms for multiple applications are produced by it. But it is mandatory to know the tricks and techniques of reinforcement learning.

Today we brought a solution of all this in a form of a book name Reinforcement learning python pdf. This book is extremely helpful for understanding reinforcement learning and its practical application.

Reinforcement learning python pdf

Book Description:

  • Reinforcement learning python PDFis best for those who want to learn robotics. The content of this book will help you to understand from basics to masters of reinforcement learning.
  • Reinforcement learning with other types of learning has explained in this book.
  • A brief guide to Markov decision processes has been explained too.
  • Q learning secrets has been shared in this wonderful yet informative book.
  • Dynamics related to programming are also a part of the book content.
  • Simulated environment and policies have been also discussed in the text.
  • There is no need to have a degree. You can be an awesome developer if you have a will to learn and enhance your skills. Go through the content of this book to be an expert developer.
  • The author tried you to explain them in the most simple and non-technical way. But the algorithms, applications, and elements have been explained comprehensively.
  • Python implementations have been explained in an amazing way.
  • This book is best for those who want to learn AL without jumping in the hassle of technical issues.

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Table of Content

Go through this content table to get an idea about what you will learn from this book.

  1. Formulating a reinforcement learning problem
  2. Comparison with other machine learning methodologies
  3. Framework for solving Reinforcement learning problems
  4. An implementation of Reinforcement Learning
  5. Increasing the complexity
  6. Peek into recent RL advancements
  7. Additional Resources

Note:

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