01 — Supervised Learning
Models that learn a mapping from inputs to targets from labelled training data.
Sublayers
01 — Linear Models and GLMs
Ordinary least squares, Ridge, Lasso, logistic regression, and generalised linear models.
02 — Tree-Based Models
Decision trees, random forests, gradient boosting (XGBoost, LightGBM).
03 — Kernel Methods
Support vector machines, kernel trick, SVR, kernel ridge regression.
04 — Instance-Based Methods
K-nearest neighbours, locally weighted regression.