I've graduated with a math major in undergrad, but mostly focused on algebra (Galois Theory, Knot theory, etc.). I work in something unrelated right now, but now I want to study machine learning. The question is, what kind of knowledge should I have if I want to really understand machine learning?
Say, here are some things I can think of, but obviously I'm missing a lot, I'm assuming.
- "Fundamentals" (Calculus, Linear Algebra, Discrete Mathematics, Coding, etc.)
- Probability (but what specific areas?)
- Statistics (but what kind?)
- Differential Equations
But what else? Or what subfields of what I've mentioned above are particularly important (i.e. Bayesian statistics)?
Edit: I am currently considering a graduate program in ML, and wanted to know if this is something I really want to do / know more about it / prepare myself.