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You're reading from  PyTorch 1.x Reinforcement Learning Cookbook

Product typeBook
Published inOct 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781838551964
Edition1st Edition
Languages
Python
Tools
PyTorch
Concepts
Reinforcement Learning
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Author (1)
Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
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Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.
Read more about Yuxi (Hayden) Liu

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To get the most out of this book

Data scientists, machine learning engineers, and AI researchers looking for quick solutions to different problems in reinforcement learning will find this book useful. Prior exposure to machine learning concepts is required, while previous experience with PyTorch is not required but will be a bonus.

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You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

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  1. Log in or register at www.packt.com.
  2. Select the Support tab.
  3. Click on Code Downloads.
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The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/PyTorch-1.x-Reinforcement-Learning-Cookbook. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

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Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "By saying empty, it doesn't mean all elements have a value of Null."

A block of code is set as follows:

>>> def random_policy():
...     action = torch.multinomial(torch.ones(n_action), 1).item()
...     return action

Any command-line input or output is written as follows:

conda install pytorch torchvision -c pytorch

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "This approach is called random search, since the weight is randomly picked in each trial with the hope that the best weight will be found with a large number of trials."

Warnings or important notes appear like this.
Tips and tricks appear like this.
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PyTorch 1.x Reinforcement Learning Cookbook
Published in: Oct 2019Publisher: PacktISBN-13: 9781838551964
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.
Read more about Yuxi (Hayden) Liu

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