Distributions, Bayes, and information theory for ML
Coin flips, bell curves, and the math of uncertainty
Updating beliefs with evidence
Mean, variance, standard deviation, and the Central Limit Theorem
Maximum likelihood and maximum a posteriori — why training works
Measuring surprise, uncertainty, and prediction quality
Measuring how different two distributions are