Deep Reinforcement Learning in Action /

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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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Brown, Brandon (Autor), Zai, Alexander (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Manning Publications, 2020.
Edición:1st edition.
Temas:
Machine learning.
Artificial intelligence.
Computational learning theory.
Reinforcement learning.
Algorithms.
Artificial Intelligence
Algorithms
Machine Learning
Apprentissage automatique.
Intelligence artificielle.
Théorie de l'apprentissage informatique.
Apprentissage par renforcement (Intelligence artificielle)
Algorithmes.
artificial intelligence.
algorithms.
Reinforcement learning
Machine learning
Computational learning theory
Artificial intelligence
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario: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.
Descripción Física:1 online resource (384 pages)

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