Who We Are

We are Sylvain and Jeremy, your guides on this journey. We hope that you will find us well suited for this position.

Jeremy has been using and teaching machine learning for around 30 years. He started using neural networks 25 years ago. During this time, he has led many companies and projects that have machine learning at their core, including founding the first company to focus on deep learning and medicine, Enlitic, and taking on the role of President and Chief Scientist of the world’s largest machine learning community, Kaggle. He is the co-founder, along with Dr. Rachel Thomas, of fast.ai, the organization that built the course this book is based on.

From time to time you will hear directly from us, in sidebars like this one from Jeremy:

J: Hi everybody, I’m Jeremy! You might be interested to know that I do not have any formal technical education. I completed a BA, with a major in philosophy, and didn’t have great grades. I was much more interested in doing real projects, rather than theoretical studies, so I worked full time at a management consulting firm called McKinsey and Company throughout my university years. If you’re somebody who would rather get their hands dirty building stuff than spend years learning abstract concepts, then you will understand where I am coming from! Look out for sidebars from me to find information most suited to people with a less mathematical or formal technical background—that is, people like me…

Sylvain, on the other hand, knows a lot about formal technical education. In fact, he has written 10 math textbooks, covering the entire advanced French maths curriculum!

S: Unlike Jeremy, I have not spent many years coding and applying machine learning algorithms. Rather, I recently came to the machine learning world, by watching Jeremy’s fast.ai course videos. So, if you are somebody who has not opened a terminal and written commands at the command line, then you will understand where I am coming from! Look out for sidebars from me to find information most suited to people with a more mathematical or formal technical background, but less real-world coding experience—that is, people like me…

The fast.ai course has been studied by hundreds of thousands of students, from all walks of life, from all parts of the world. Sylvain stood out as the most impressive student of the course that Jeremy had ever seen, which led to him joining fast.ai, and then becoming the coauthor, along with Jeremy, of the fastai software library.

All this means that between us you have the best of both worlds: the people who know more about the software than anybody else, because they wrote it; an expert on math, and an expert on coding and machine learning; and also people who understand both what it feels like to be a relative outsider in math, and a relative outsider in coding and machine learning.

Anybody who has watched sports knows that if you have a two-person commentary team then you also need a third person to do “special comments.” Our special commentator is Alexis Gallagher. Alexis has a very diverse background: he has been a researcher in mathematical biology, a screenplay writer, an improv performer, a McKinsey consultant (like Jeremy!), a Swift coder, and a CTO.

A: I’ve decided it’s time for me to learn about this AI stuff! After all, I’ve tried pretty much everything else… But I don’t really have a background in building machine learning models. Still… how hard can it be? I’m going to be learning throughout this book, just like you are. Look out for my sidebars for learning tips that I found helpful on my journey, and hopefully you will find helpful too.