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|a 518.1
|2 23
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|a UAMI
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|a Brown, Brandon,
|e author.
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|a Deep Reinforcement Learning in Action /
|c Brown, Brandon.
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|a 1st edition.
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|b Manning Publications,
|c 2020.
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|a 1 online resource (384 pages)
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|a text
|b txt
|2 rdacontent
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|a text file
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|a Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and playing video games. Along the way, you'll work with core algorithms, including deep Q-networks and policy gradients, along with industry-standard tools like PyTorch and OpenAI Gym.
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|f © 2020 Manning Publications Co. All rights reserved.
|g 2020
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|a Made available through: Safari, an O'Reilly Media Company.
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|a Online resource; Title from title page (viewed March 29, 2020)
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
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|a Machine learning.
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650 |
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|a Artificial intelligence.
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650 |
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|a Computational learning theory.
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|a Reinforcement learning.
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|a Algorithms.
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|a Artificial Intelligence
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|a Algorithms
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|a Machine Learning
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650 |
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|a Apprentissage automatique.
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650 |
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|a Intelligence artificielle.
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650 |
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|a Théorie de l'apprentissage informatique.
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650 |
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|a Apprentissage par renforcement (Intelligence artificielle)
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650 |
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|a Algorithmes.
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|a artificial intelligence.
|2 aat
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|a algorithms.
|2 aat
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|a Reinforcement learning
|2 fast
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|a Machine learning
|2 fast
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650 |
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7 |
|a Computational learning theory
|2 fast
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650 |
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7 |
|a Artificial intelligence
|2 fast
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650 |
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7 |
|a Algorithms
|2 fast
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1 |
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|a Zai, Alexander,
|e author.
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710 |
2 |
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|a Safari, an O'Reilly Media Company.
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856 |
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|u https://learning.oreilly.com/library/view/~/9781617295430/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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