How did you get from Physics into ML?
Today’s Machine Learning is very much an empirical profession, which means that we learn simply by experimentation, using the scientific method. Much of what I’ve been doing as a Physicist was empirical as well, and that experience prepared me well for working in ML. However, besides the skills needed, the more important part is networking: I was lucky enough to meet my future manager from JP Morgan Chase at a networking event hosted by the University of Chicago while I was still a postdoc.

Why do you write?
I mostly write to learn. This is also known as the Feynman technique. If you can’t write it down in a paragraph, that means that you probably haven’t understood it well enough yet. Besides, writing for an audience online is a great way to build a brand and create visibility for future opportunities. It’s an investment.

Do you have any tips for getting started with writing?
Yes! Check out my post here:
6 Simple Lessons That Will Help You Start Your Writing Side Gig

What’s the architecture of this site?
It’s using Jekyll, Github Pages, and a Google domain. You can find the source code on my github.

What’s the best way to get in touch?
You can find me on LinkedIn.

What are some questions that you’re being asked a frequently?
Check out this link.