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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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."