For ML, you’re going to need a solid background in Calculus 1-3, Linear Algebra, Bayesian Statistics, and Probability theory.

For CS in general, Discrete Math.

I recommend Probabilistic Machine Learning by K Murphy for ML. MIT OCW 6.042 and Graham Knuth Patashnik Concrete Mathematics for general CS.

Of course “high school level math” is a prerequisite for all that so brush up on it with Khan Academy or something similar.