Understanding Machine Learning

Un­der­stand­ing Ma­chine Learn­ing (I)

Un­der­stand­ing Ma­chine Learn­ing (II)

Un­der­stand­ing Ma­chine Learn­ing (III)

UML IV: Lin­ear Predictors

UML V: Con­vex Learn­ing Problems

UML VI: Stochas­tic Gra­di­ent Descent

UML VII: Meta-Learning

UML VIII: Lin­ear Pre­dic­tors (2)

UML IX: Ker­nels and Boosting

A Sim­ple In­tro­duc­tion to Neu­ral Networks

UML XI: Near­est Neigh­bor Schemes

UML XII: Di­men­sion­al­ity Reduction

UML XIII: On­line Learn­ing and Clustering

UML final