CmpE 544 Pattern Recognition

Fall Semester 2014-2015



Introduction to Machine Learning 3e, The MIT Press, 2014. It's fine if you have a copy of the first edition or the second edition, or its Turkish translation.


  1. Chap 1. Introduction
  2. Chap 2. Supervised Learning
  3. Chap 3. Bayesian Decision Theory
  4. Chap 4. Parametric Methods
  5. Chap 5. Multivariate Methods
  6. Chap 6. Dimensionality Reduction
  7. Chap 7. Clustering
  8. Chap 8. Nonparametric Methods
  9. Chap 9. Decision Trees
  10. Chap 13. Hidden Markov Models


There will be 4-5 computer howeworks. I recommend using Matlab.


To introduce the student to the problems related to pattern recognition and discuss how solutions may be attempted using statistical techniques. This course is followed by and is a prerequisite for CmpE 545 Artificial Neural Networks.

Prerequisite by Topic

Undergraduate level calculus, probability theory. Prior experience in a high-level programming language.

Computer Usage

Almost all homeworks require computer simulations. I recommend using Matlab.


1 Project 0.30

1 Final 0.30

Homeworks 0.40

Last modified on Oct 1, 2014.