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Applied Reinforcement Learning with Python

With OpenAI Gym, Tensorflow, and Keras
BuchKartoniert, Paperback
168 Seiten
Englisch
Springererschienen am24.08.20191st ed.
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 LearnImplement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and KerasDeploy and train reinforcement learning-based solutions via cloud resourcesApply 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.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR48,14
E-BookPDF1 - PDF WatermarkE-Book
EUR46,99

Produkt

KlappentextDelve 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 LearnImplement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and KerasDeploy and train reinforcement learning-based solutions via cloud resourcesApply 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.
Zusammenfassung
Details
ISBN/GTIN978-1-4842-5126-3
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2019
Erscheinungsdatum24.08.2019
Auflage1st ed.
Seiten168 Seiten
SpracheEnglisch
Gewicht289 g
IllustrationenXV, 168 p. 47 illus.
Artikel-Nr.46764784

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr

Autor

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.