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Titlebook: Reinforcement Learning; With Open AI, Tensor Abhishek Nandy,Manisha Biswas Book 2018 Abhishek Nandy and Manisha Biswas 2018 Reinforcement

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發(fā)表于 2025-3-21 19:01:05 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Reinforcement Learning
副標(biāo)題With Open AI, Tensor
編輯Abhishek Nandy,Manisha Biswas
視頻videohttp://file.papertrans.cn/826/825931/825931.mp4
概述Discusses Open AI and Open AI Gym with relevance to reinforcement learning.Application of TensorFlow and Keras to reinforcement learning.Swarm Intelligence with Python in terms of reinforcement learni
圖書封面Titlebook: Reinforcement Learning; With Open AI, Tensor Abhishek Nandy,Manisha Biswas Book 2018 Abhishek Nandy and Manisha Biswas  2018 Reinforcement
描述Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process.?.Reinforcement Learning.?discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI ?before looking at Open AI Gym. You’ll then learn about Swarm Intelligence with Python in terms of reinforcement learning..?.The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There’s also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you‘ll delve into Google’s Deep Mind and see scenarios where reinforcement learning can be used.?.What You‘ll Learn?.Absorb the core concepts of the reinforcement learning process.Use advanced topics of deep learning and AI.Work with Open AI Gym, Open AI, and Pytho
出版日期Book 2018
關(guān)鍵詞Reinforcement Learning; Artificial Intelligence; Python; TensorFlow; Keras; Deep Learning; Machine Learnin
版次1
doihttps://doi.org/10.1007/978-1-4842-3285-9
isbn_softcover978-1-4842-3284-2
isbn_ebook978-1-4842-3285-9
copyrightAbhishek Nandy and Manisha Biswas 2018
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書目名稱Reinforcement Learning影響因子(影響力)




書目名稱Reinforcement Learning影響因子(影響力)學(xué)科排名




書目名稱Reinforcement Learning網(wǎng)絡(luò)公開(kāi)度




書目名稱Reinforcement Learning網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Reinforcement Learning被引頻次




書目名稱Reinforcement Learning被引頻次學(xué)科排名




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rm Intelligence with Python in terms of reinforcement learniMaster reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related
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Applying Python to Reinforcement Learning,h analysis of Reinforcement Learning. We start off by going through Q learning in terms of Python. Then we describe Swarm intelligence in Python, with an introduction to what exactly Swarm intelligence is. The chapter also covers the Markov decision process (MDP) toolbox.
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Book 2018ain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process.?.Reinforcement Learning.?discusses algorithm implementations important for reinforcement learning, including Mark
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https://doi.org/10.1007/978-1-4842-3285-9Reinforcement Learning; Artificial Intelligence; Python; TensorFlow; Keras; Deep Learning; Machine Learnin
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