CmpE 544 Pattern Recognition

Fall Semester

Ethem ALPAYDIN

Textbook

Introduction to Machine Learning, The MIT Press, 2004. Check if the book is available at the Library.

Topics

  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

Homeworks

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

Goals

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.

Grading

·  1 Project 0.30

·  1 Final 0.30

·  Homeworks 0.40

Last modified on Sep  22, 2008.