Not sure you need any maths for Kaggle competitions. Learn XGBoost and random forests for regression and classifications and learn how to evaluate the models an

Not sure you need any maths for Kaggle competitions. Learn XGBoost and random forests for regression and classifications and learn how to evaluate the models and some of the tricks for coercing different types of data into them for good peformance. Then curve fit on various data to your heart's content. It'll take ages before you need maths more complicated than arithmetic. Taking a stats course won't help you at all. The way canned ML algorithms work has nothing whatsoever to do with data generating models which is what stats is about. You'll start to need maths when it comes to dimensionality reduction and embedding and that'll come in the form of 95% linear algebra and 5% calculus. Still no stats though. Wayyyy down the line if you get into the information theoretic view, or pick up the fetish of justifying everything via a Bayesian methodology then you'll need lots of stats.