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Applied reinforcement learning with ...

Beysolow, Taweh.

Applied reinforcement learning with Pythonwith OpenAI Gym, Tensorflow, and Keras /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applied reinforcement learning with Pythonby Taweh Beysolow II.
Reminder of title:	with OpenAI Gym, Tensorflow, and Keras /
Author:	Beysolow, Taweh.
Published:	Berkeley, CA :Apress :2019.
Description:	xv, 168 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Reinforcement learning.
Online resource:	https://doi.org/10.1007/978-1-4842-5127-0
ISBN:	9781484251270$q(electronic bk.)

Applied reinforcement learning with Pythonwith OpenAI Gym, Tensorflow, and Keras /
Beysolow, Taweh.

Applied reinforcement learning with Pythonwith OpenAI Gym, Tensorflow, and Keras /[electronic resource] :by Taweh Beysolow II. - Berkeley, CA :Apress :2019. - xv, 168 p. :ill., digital ;24 cm.

Chapter 1: Introduction to Reinforcement Learning -- Chapter 2: Reinforcement Learning Algorithms -- Chapter 3: Q Learning -- Chapter 4: Reinforcement Learning Based Market Making -- Chapter 5: Reinforcement Learning for Video Games.

Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym. Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through features of OpenAI Gym, from utilizing standard libraries to creating your own environments, then discover how to frame reinforcement learning problems so you can research, develop, and deploy RL-based solutions. What You'll Learn: Implement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras Deploy and train reinforcement learning-based solutions via cloud resources Apply practical applications of reinforcement learning.

ISBN: 9781484251270$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-5127-0doiSubjects--Uniform Titles:

OpenAI Gym.
Subjects--Topical Terms:

349131
Reinforcement learning.

LC Class. No.: Q325.6 / .B49 2019

Dewey Class. No.: 006.31

Applied reinforcement learning with Pythonwith OpenAI Gym, Tensorflow, and Keras /
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505 0 $a Chapter 1: Introduction to Reinforcement Learning -- Chapter 2: Reinforcement Learning Algorithms -- Chapter 3: Q Learning -- Chapter 4: Reinforcement Learning Based Market Making -- Chapter 5: Reinforcement Learning for Video Games.
520 $a Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym. Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through features of OpenAI Gym, from utilizing standard libraries to creating your own environments, then discover how to frame reinforcement learning problems so you can research, develop, and deploy RL-based solutions. What You'll Learn: Implement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras Deploy and train reinforcement learning-based solutions via cloud resources Apply practical applications of reinforcement learning.
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