(ML 2.6) Bootstrap aggregation (Bagging)

(ML 1.1) Machine learning - overview and applications

(ML 1.2) What is supervised learning?

(ML 1.3) What is unsupervised learning?

(ML 1.4) Variations on supervised and unsupervised

(ML 1.5) Generative vs discriminative models

(ML 1.6) k-Nearest Neighbor classification algorithm

(ML 2.1) Classification trees (CART)

(ML 2.2) Regression trees (CART)

(ML 2.3) Growing a regression tree (CART)

(ML 2.4) Growing a classification tree (CART)

(ML 2.5) Generalizations for trees (CART)

(ML 2.6) Bootstrap aggregation (Bagging)