TTIC 31020: Introduction to Machine Learning

November 22, 2022

Topics

• Optimal Classification
• Lect 01 - 02: Linear Regression
• Lect 03: Perceptron, Multiway, Convergence
• Lect 04: Logistic Regression, Error Decomp, Likelihood
• Lect 05 - 07: Regularization
• Lect 08: SVM
• Lect 09 - 10: Generative Models and EV Algo
• Lect 11 - 12: Decision Tree and ensemble
  • Ada-boost (keep historical error), and stepwise regression (fit to residue).
  • Bagging (bootstrap N samples with replacesment, sampling features, select d random features).
• Lect 13: Information Theory

• Lecture 14 - 16: Deep Learning

• Information Theory
• Deep Learning