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    TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Autor:
    Palanisamy P
    TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - okladka książki

    TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - okladka książki

    TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - audiobook MP3

    TensorFlow 2 Reinforcement Learning Cookbook. Over 50 recipes to help you build, train, and deploy learning agents for real-world applications Palanisamy P - audiobook CD

    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    472
    Dostępne formaty:
         PDF
         ePub
         Mobi
    With deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications.
    Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you’ll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x.
    By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch.

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    O autorze książki

    Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.

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