Tools from Probability: Concentration Inequalities
The Statistical Learning Framework.
Probably Approximately Correct (PAC) Learning - Part 1.
Probably Approximately Correct (PAC) Learning - Part 2.
Probably Approximately Correct (PAC) Learning - Part 3.
The Vapnik-Chervonenkis (VC) Dimension - Part 1.
The Vapnik-Chervonenkis (VC) Dimension - Part 2.
Linear Classifiers and Perceptron Algorithm - Part 1.
Bias/Complexity tradeoff and intro to Boosting.
Intro to General Learning Model (Linear Regression).
Convex, Lipschitz functions and Basic Gradient Descent Algorithm.
Regularized Loss Minimization and Stability - Part 1.