- HW1: Regression problem - Lagrange polynomial, OLS method, Gradient descent, Spline approximation
- HW2: Classification problem - KNN from scratch, "K-closest neighbours" using Parzen windows, outlier detection using strange algo, unknown to the English-speaking community
- HW3: Metric methods for regression problem - Nadaraya-Watson kernel-weighted average and local regression smoothing with LOWESS algo
- HW4: Decision trees: CART from skratch, decision rules set covering machine struggle
eddiekro / ml_univ Goto Github PK
View Code? Open in Web Editor NEWAnother Machine Learning University course. This time we focus on implementing basic models&concepts rather than using them in real life