Details for: Ravichandiran S.Hands-On Reinforc. Learning with Python 2018

Ravichandiran S.Hands-On Reinforc. Learning with Python 2018

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15.51 MiB (16264361 Bytes)

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2019-09-02

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andryold1  

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46BC97C9EDE7F50B72765E8B85A2BAFF1344D707

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Textbook in PDF format A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python. Key Features Enter the world of artificial intelligence using the power of Python. An example-rich guide to master various RL and DRL algorithms. Explore various state-of-the-art architectures along with math. Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence (AI). Hands-On Reinforcement Learning with Python will help you master not only basic reinforcement learning algorithms but also advanced deep reinforcement learning (DRL) algorithms. The book starts with an introduction to reinforcement learning followed by OpenAI Gym and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov decision process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning. By the end of this book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence

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1. Ravichandiran S. Hands-On Reinforcement Learning with Python 2018.pdf15.51 MiB