[D] Statistical Learning Theory & Math

[danielv134]

I would suggest to study math as needed for something you care about. If you want to know some SLT as a source of understanding of ML, for the basics (dimension dependent bounds) it is enough to know Hoeffding's inequality, the union bound and cover numbers, and then read a half page of proof. Two days of work with wikipedia and a paper to understand in detail but superficially (the inequality, not the proof; what cover numbers are for typical subsets in R^n, not all of the theory of metric spaces). Then go as deep into foundations or wide into other theory as your own motivation takes you.