Machine Learning
Historical Context
Early Probability
Statistical Modeling
Computing History
Probability Theory
Kolmogorov Axioms
Conditional Probability
Independence
Bayes Estimator
Information Theory
Entropy
Conditional Entropy
Mutual Information
KL Divergence
ML Types
Supervised Learning
Reinforcement Learning
Unsupervised Learning
Loss Functions
Mean Squared Error
Classification Accuracy
Empirical Risk
Bayes Risk
Regret & Reconstruction