Setting up the working environment

Let's get started with setting up the working environment, including the correct versions of Python and Anaconda, and PyTorch as the main framework that is used throughout the book.

Python is the language we use to implement all reinforcement learning algorithms and techniques throughout the book. In this book, we will be using Python 3, or more specifically, 3.6 or above. If you are a Python 2 user, now is the best time for you to switch to Python 3, as Python 2 will no longer be supported after 2020. The transition is very smooth, though, so don't panic.

Anaconda is an open source Python distribution (www.anaconda.com/distribution/) for data science and machine learning. We will be using Anaconda's package manager, conda, to install Python packages, along with pip.

PyTorch (https://pytorch.org/), primarily developed by the Facebook AI Research (FAIR) Group, is a trendy machine learning library based on Torch (http://torch.ch/). Tensors in PyTorch replace NumPy's ndarrays, which provides more flexibility and compatibility with GPUs. Because of the powerful computational graphs and the simple and friendly interface, the PyTorch community is expanding on a daily basis, and it has seen heavy adoption by more and more tech giants.

Let's see how to properly set up all of these components.