Preface

Artificial intelligence (AI) is here and has become a powerful force that is fueling modern applications that are used on a daily basis. Much like the discovery/invention of fire, the wheel, oil, electricity, and electronics, AI is reshaping our world in ways that we could only fantasize about. AI has been historically a niche computer science subject, offered by a handful of labs. But because of the explosion of excellent theory, an increase in computing power, and the availability of data, the field started growing exponentially in the 2000s and has shown no sign of slowing down anytime soon.

AI has proven again and again that given the right algorithm and enough amount of data, it can learn a task by itself with limited human intervention and produce results that rival human judgement and sometimes even surpass them. Whether you are a rookie learning the ropes or a veteran driving a large organization, there is every reason to understand how AI works. Neural networks (NNs) are some of the most flexible types of AI algorithms that have been adapted to a vast range of applications, including structured data, text, and vision domains.

This book starts with the basics of NNs and covers over 40 applications of computer vision using PyTorch. By mastering these applications, you will be well-equipped to build NNs for a variety of use cases in various domains, such as automotive, security, back-offices of finance, healthcare, and beyond. The skills acquired will empower you to not only implement state-of-the-art solutions but also innovate and develop new applications that address more real-world challenges.

Ultimately, this book serves as a bridge between academic learning and practical application, enabling you to move forward with confidence and make significant contributions throughout your professional career.