Cmpe 462 - Machine Learning

This course provides an overview of artificial learning systems. The course is designed as undergraduate level introductory to machine learning concepts. The schedule includes broad overview of many concepts and algorithms.

The course mainly follows Introduction to Machine Learning, Ethem Alpaydin, 3e, The MIT Press, 2014.

  1. Introduction to Machine Learning.
  2. Probability Review
  3. Bayesian Decision Theory
  4. Parametric Methods
  5. Multivariate Data
  6. Dimensionality Reduction
  7. Clustering
  8. Non-parametric Methods
  9. Neural Networks
  10. Decision Trees
  11. Support Vector Machines
  12. Reinforcement Learning
  13. Design and Analysis of Machine Learning Methods

Course page of last available semester: Spring 2017
All offered years can be found here