front matter

 

preface

Thank you for buying our book. We hope that it provides you with a look under the hood of deep learning (DL) and gives you some inspirations on how to use probabilistic DL methods for your work.

All three of us, the authors, have a background in statistics. We started our journey in DL together in 2014. We got so excited about it that DL is still in the center of our professional lives. DL has a broad range of applications, but we are especially fascinated by the power of combining DL models with probabilistic approaches as used in statistics. In our experience, a deep understanding of the potential of probabilistic DL requires both insight into the underlying methods and practical experience. Therefore, we tried to find a good balance of both ingredients in this book.

In this book, we aimed to give some clear ideas and examples of applications before discussing the methods involved. You also have the chance to make practical use of all discussed methods by working with the accompanying Jupyter notebooks. We hope you learn as much by reading this book as we learned while writing it. Have fun and stay curious!

acknowledgments

about this book

Who should read this book

How this book is organized: A roadmap

About the code

liveBook discussion forum

about the authors

about the cover illustration