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DeepReinforcementLearningHands-On_Applym.epub

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Deep Reinforcement Learning Hands-On Table of Contents Deep Reinforcement Learning Hands-On Why subscribe? PacktPub.com Contributors About the author About the reviewers Packt is Searching for Authors Like You Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews 1. What is Reinforcement Learning? Learning – supervised, unsupervised, and reinforcement RL formalisms and relations Reward The agent The environment Actions Observations Markov decision processes Markov process Markov reward process Markov decision process Summary 2. OpenAI Gym The anatomy of the agent Hardware and software requirements OpenAI Gym API Action space Observation space The environment Creation of the environment The CartPole session The random CartPole agent The extra Gym functionality – wrappers and monitors Wrappers Monitor Summary 3. Deep Learning with PyTorch Tensors Creation of tensors Scalar tensors Tensor operations GPU tensors Gradients Tensors and gradients NN building blocks Custom layers Final glue – loss ......

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