I believe all of these topics are extremely important since they provide the fundamentals of machine learning algorithms. In linear algebra, you want to ensure that you focus on matrices and vectors, notation, and operations. For statistics, I believe combinatorics, probability, Bayes' Theorem, variance and expectation, and conditional, joint, and standard distributions are all important. There's so many things to cover within all of these math topics and I hope this helps!