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Обучение с подкреплением (Reinforcement Learning)

Учебно-методические материалы

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Packt Publishing, 2017. — 336 p. Master different reinforcement learning techniques and their practical implementation using OpenAI Gym, Python and Java Reinforcement learning (RL) is becoming a popular tool for constructing autonomous systems that can improve themselves with experience. We will break the RL framework into its core building blocks, and provide you with details of...
  • №1
  • 198,65 КБ
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Packt Publishing, 2021. — 484 p.— ISBN 1838644148, 9781838644147. Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key Features - Understand how large-scale state-of-the-art RL algorithms and approaches work -...
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  • 151,72 КБ
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Packt Publishing, 2018. — 546 p. — ISBN: 978-1788834247. !Code files only This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep reinforcement learning (RL), from the first principles to the latest algorithms Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy...
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  • 5,55 МБ
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Packt Publishing, 2021. — 472 p. — ISBN 9781838982546. Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key Features Develop and deploy deep reinforcement learning-based solutions to production pipelines, products, and services Explore popular reinforcement learning algorithms such as Q-learning,...
  • №4
  • 7,59 МБ
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Packt, 2018. — 318 p. — ISBN13: 978-1-78883-652-4. A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the...
  • №5
  • 42,84 МБ
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Packt Publishing, 2018. — 287 p. — ISBN: 978-1-78899-161-2. Code files only! Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Reinforcement learning is one of the most exciting and rapidly growing fields in machine learning. This is due to the many novel algorithms developed and incredible results published in recent...
  • №6
  • 1,31 МБ
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