Why this book?

As with most of the books that I have written, this book is the result of my professional experience and personal frustration of not having resources like these out there. More specifically, this book was motiviated by the lack of a text that I could refer my students to so they could learn about how various matrix algebra concepts are connected with statistical ideas.

Likewise, throughout my teaching activities to different user profiles, I’ve seen time and again that we are not trained to see the connections between many analytical notions, and their matrix-geometric interpretation.

This book is my attempt to provide a resource for future (and current) data scientists that may have the software know-how, and a strong understanding of the working principles of the techniques they use, yet they have gaps at the matrix algebra level that prevents them to fully grasp the “under the hood” principles of their daily tools.

My hope is that the concepts and notions described in this text will allow you to get a good grasp of the methods discussed in any textbook about Statistical Learning, and how they work. I’m sure this book will be a great resource and consulting text for undergraduate and graduate students, as well as data scientists in the more general sense of this term.