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
Who This Book Is For
Data scientists, machine learning engineers and software engineers familiar with machine learning and deep learning concepts.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
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.
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:
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Books From California, Simi Valley, CA, USA
paperback. Zustand: Very Good. Artikel-Nr. mon0003868736
Anzahl: 1 verfügbar
Anbieter: Books From California, Simi Valley, CA, USA
paperback. Zustand: Good. Artikel-Nr. mon0003911322
Anzahl: 2 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 168 pages. 9.00x6.00x0.50 inches. In Stock. Artikel-Nr. x-1484251261
Anzahl: 2 verfügbar
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2019. 1st ed. paperback. . . . . . Books ship from the US and Ireland. Artikel-Nr. V9781484251263
Anzahl: 15 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: 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. Artikel-Nr. 9781484251263
Anzahl: 2 verfügbar