grokking deep reinforcement learning von morales miguel (25 Ergebnisse)

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Paperback. Zustand: New. Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required.   Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.   We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.   . Foundational reinforcement learning concepts and methods . The most popular deep reinforcement learning agents solving high-dimensional environments . Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence   Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

Zustand: New. &Uumlber den AutorMiguel Morales is a Senior Software Engineer at Lockheed Martin, Missile and Fire Control-Autonomous Systems. He is also a faculty member at Georgia Institute of Technology where he works as an Instructional Ass.

Paperback. Zustand: New. Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required.   Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.   We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.   . Foundational reinforcement learning concepts and methods . The most popular deep reinforcement learning agents solving high-dimensional environments . Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence   Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

Taschenbuch. Zustand: Neu. Neuware - Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.

Paperback. Zustand: New. Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required.   Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.   We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.   . Foundational reinforcement learning concepts and methods . The most popular deep reinforcement learning agents solving high-dimensional environments . Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence   Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

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Paperback. Zustand: New. Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required.   Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.   We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.   . Foundational reinforcement learning concepts and methods . The most popular deep reinforcement learning agents solving high-dimensional environments . Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence   Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

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Paperback. Zustand: Brand New. 450 pages. 9.25x7.25x1.00 inches. In Stock.

Zustand: New. 2020. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Paperback. Zustand: Brand New. 450 pages. 9.25x7.25x1.00 inches. In Stock.

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Paperback. Zustand: new. Paperback. Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Foundational reinforcement learning concepts and methods The most popular deep reinforcement learning agents solving high-dimensional environments Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Zustand: new. Paperback. Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Foundational reinforcement learning concepts and methods The most popular deep reinforcement learning agents solving high-dimensional environments Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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