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Published by Packt Publishing 2019-07, 2019
ISBN 10: 1789344158 ISBN 13: 9781789344158
Language: English
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Published by Packt Publishing 2018-06, 2018
ISBN 10: 1788836529 ISBN 13: 9781788836524
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Published by Packt Publishing (edition ), 2018
ISBN 10: 1789534208 ISBN 13: 9781789534207
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Published by Packt Publishing 2021-01, 2021
ISBN 10: 1838821597 ISBN 13: 9781838821593
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Published by Packt Publishing 2018-12, 2018
ISBN 10: 1789534208 ISBN 13: 9781789534207
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Published by Packt Publishing 2020-09, 2020
ISBN 10: 1839210680 ISBN 13: 9781839210686
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Published by Packt Publishing 6/28/2018, 2018
ISBN 10: 1788836529 ISBN 13: 9781788836524
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Add to basketPaperback or Softback. Condition: New. Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow 1.21. Book.
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Published by Packt Publishing 2019-04-18, 2019
ISBN 10: 1838649778 ISBN 13: 9781838649777
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Published by Packt Publishing 1/22/2021, 2021
ISBN 10: 1838821597 ISBN 13: 9781838821593
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Add to basketPaperback or Softback. Condition: New. Getting Started with Google BERT: Build and train state-of-the-art natural language processing models using BERT 1.33. Book.
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Published by Packt Publishing Limited, United Kingdom, Birmingham, 2023
ISBN 10: 1788836529 ISBN 13: 9781788836524
Language: English
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Paperback. Condition: Very Good. A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python About This Book Your entry point into 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 Who This Book Is For If you're a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book. What You Will Learn Understand the basics of reinforcement learning methods, algorithms, and elements Train an agent to walk using OpenAI Gym and Tensorflow Understand the Markov Decision Process, Bellman's optimality, and TD learning Solve multi-armed-bandit problems using various algorithms Master deep learning algorithms, such as RNN, LSTM, and CNN with applications Build intelligent agents using the DRQN algorithm to play the Doom game Teach agents to play the Lunar Lander game using DDPG Train an agent to win a car racing game using dueling DQN In Detail 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 advanced deep reinforcement learning 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 the 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. Style and approach This is a hands-on book designed to further expand your machine learning skills by understanding reinforcement to deep reinforcement learning algorithms with applications in Python. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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