## CmpE 544 Pattern
Recognition

### Fall Semester 2014-2015

### Ethem ALPAYDIN

### Textbook

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.

### Topics

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

### Homeworks

There will be
4-5 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 Oct 1, 2014.*