Ask HN: What Math topics are the most important for Machine Learning?

I'm just beginning to learn Math for ML, with no background(other than high school). I see that Linear Algebra, Calculus, Probability, and Statistics are the most important areas I should be learning, but turns out these are pretty wide fields that can take years to master.

So I'm trying to make a curriculum of the most important subjects from each of these fields that I need to learn. By "most important" I mean most useful for applying ML on practice. Can you help me out?