Applied Reinforcement Learning with Python by Taweh Beysolow Ii

Applied Reinforcement Learning with Python by Taweh Beysolow Ii

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Applied Reinforcement Learning with Python by Taweh Beysolow Ii

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   Who This Book Is For  Data scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts.
Taweh Beysolow II is a data scientist and author currently based in the United States. He has a Bachelor of Science degree in economics from St. Johns University and a Master of Science in Applied Statistics from Fordham University. After successfully exiting the startup he co-founded, he now is a Director at Industry Capital, a San Francisco based Private Equity firm, where he helps lead the Cryptocurrency and Blockchain platforms.
SKU Unavailable
ISBN 13 9781484251263
ISBN 10 1484251261
Title Applied Reinforcement Learning with Python
Author Taweh Beysolow Ii
Condition Unavailable
Binding Type Paperback
Publisher APress
Year published 2019-08-24
Number of pages 168
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note Unavailable