Preface
PyTorch Deep Learning Hands-On is beginner-friendly but also helps readers to get into the depths of deep learning quickly. In the last couple of years, we have seen deep learning become the new electricity. It has fought its way from academia into industry, helping resolve thousands of enigmas that humans could never have imagined solving without it. The mainstream adoption of deep learning as a go-to implementation was driven mainly by a bunch of frameworks that reliably delivered complex algorithms as efficient built-in methods. This book showcases the benefits of PyTorch for prototyping a deep learning model, for building a deep learning workflow, and for taking a prototyped model to production. Overall, the book concentrates on the practical implementation of PyTorch instead of explaining the math behind it, but it also links you to places that you could fall back to if you lag behind with a few concepts.