To get the most out of this book
This book assumes some foundational knowledge of ML, deep learning, and Python programming. Some basic working knowledge of scikit-learn and PyTorch can be helpful, although they can be learned on the go.
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Software/hardware covered in the book |
Operating system requirements |
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Google Colab |
Windows, macOS, or Linux |
For the software requirements, you have two options to execute the code provided in this book. You can choose to either run the code within Google Colab online at https://colab.research.google.com/ or download the code to your local computer and execute it there. Google Colab provides a hassle-free option as it comes with all the necessary libraries pre-installed, so you don’t need to install anything on your local machine. All you need is a web browser to access Google Colab and a Google account. If you prefer to work locally, ensure that you have Python (3.6 or higher) installed, as well as the specified libraries such as PyTorch, torchvision, NumPy, and scikit-learn. A list of required libraries can be found in the GitHub repository of the book. These libraries are compatible with Windows, macOS, and Linux operating systems. A modern GPU can speed up the code execution for the deep learning chapters that appear later in the book; however, it’s not mandatory.
If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.
Regarding references, we use numbered references such as “[6],” where you can go to the References section at the end of that chapter and download the corresponding reference (paper/blog/article) either using the link (if mentioned) or searching for that reference on Google Scholar (https://scholar.google.com/).
At the conclusion of each chapter, you will find a set of questions designed to test your comprehension of the material covered. We strongly encourage you to engage with these questions to reinforce your learning. Solutions or answers to selected questions can be found in Assessments towards the end of this book.
