About
Mission
formalML is a curated collection of deep-dive explainers on the mathematical machinery behind modern machine learning. Every topic receives a three-pillar treatment: rigorous mathematical exposition, interactive visual intuition, and working code you can run immediately.
The site exists because the gap between textbook formalism and practical ML understanding is wider than it needs to be. We believe that interactive visualization — watching a filtration sweep across a point cloud, seeing eigenvalues shift as you perturb a matrix — builds the kind of geometric intuition that no amount of static notation can provide.
Author
Jonathan Rocha is a data scientist and researcher with a background spanning mathematics, data science, and the humanities. He holds an MS in Data Science from SMU, an MA in English from Texas A&M University, and a BA in History from Texas A&M. His research interests include time-series data mining and topology-aware deep learning, and he is pursuing this project as an independent pre-doctoral research project.
DataSalt
formalml.com is an independent educational project by the founder of DataSalt LLC.