I’m Matt Jacob — statistician, distance runner, and soon-to-be math PhD student chasing the intersection of mathematics and machine learning.

Who I Am

From New York, and I’ve spent my undergrad and grad at Binghamton University — BS in Finance and Actuarial Science, MS in Statistics, and this fall will be starting a PhD in Mathematics there. Right now I work as a data analyst, where I build data pipelines, Shiny apps, etc. On the research side, I’m currently aiding a project applying ML to prognostic medicine.

Outside of math, I’m a former D1 cross country and track athlete. I still train at a pretty high level ~ 70-90 miles a week. PRs include 14:48 5K and 70:20 half marathon. If you’ve ever wondered what a lactate threshold curve looks like modeled with a third-degree polynomial, hmu…

What I’m Working Through Right Now

  • The Elements of Statistical Learning (Hastie, Tibshirani, Friedman)
  • Deep Learning (Goodfellow, Bengio, Courville)
  • Andrew Ng’s Machine Learning and Deep Learning Specializations
  • Recently finished Why Machines Learn (Ananthaswamy) and Everything is Predictable (Chivers)
  • Recently finished Lee & Seung (1999) — Learning the parts of objects by non-negative matrix factorization

I’ll write about what I’m learning in real time, this site is meant to document that.

Why “Don Q”?

The name is a reference to Don Quixote — the knight who believed so deeply in his fantasy that the fiction became his reality ( arguably not for the best, in his case).

It’s also a nod to my Puerto Rican heritage, with the handle — @DonQ.T — being NumPy syntax for a matrix transpose (I had a really late night).

What You’ll Find Here

The math behind machine learning — theory, proofs, geometry, and the code. If you’re working toward a career in ML, data science, quant research, or you’re just someone who wants to understand this stuff at a real level, come learn alongside me!

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