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Publicado por Apress, Apress Aug 2019, 2019
ISBN 10: 1484251261 ISBN 13: 9781484251263
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 48,14
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -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 PythonWork with AI frameworks such as OpenAI Gym, Tensorflow, and KerasDeploy and train reinforcement learning¿based solutions via cloud resourcesApply practical applications of reinforcement learningWho This Book Is ForData scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 184 pp. Englisch.
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 PythonWork 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 ForData scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 48,14
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 PythonWork 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 ForData scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts. 184 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 40,39
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Beginning-Intermediate|Understand how to package and deploy solutions in Python that utilize deep learningIncludes specific topics such as Q learning and deep reinforcement-learningCovers the latest reinforcement learning p.