dive into deep learning, great machine learning book that teaches the fundamentals with just the right amount of both math and code.
mit open courseware, taught me proof based calculus I-III and linear algebra (thank you, gilbert strang).
think bayes 2, example based explanations of bayesian statistics that finally sparked the epiphany going from bayes' theorem in probability to bayesian statistics.
statquest's #66DaysOfData, intuitive illustrations of statistical analysis with examples from genetics (brought to you by the friendly folks of the genetics department at UNC chapel hill!)
ritvikmath, great intuitions and solid math on statistical concepts like sampling from a distribution and markov chain monte carlo techniques.