Applied
Machine Learning

Vectors, matrices, dot product, eigenvalues — everything used in ML derivations

Distributions, expectations, Bayes theorem, MLE

Derivatives, chain rule, gradient descent derivation

Entropy, KL divergence, cross-entropy — used in loss functions