Learning outcomes

After completing the course, the student can:
- describe the basic structure of pattern recognition systems and the statistical bases of the classification theory.
- distinguish supervised learning methods from the unsupervised ones. 
- apply supervised learning methods to the classifier design.

Contents

The basic structure of pattern recognition systems. Supervised and unsupervised learning. Some most important machine learning algorithms are presented and examples are described for their applications.

Evaluation

Belongs to following study modules

2015–2016

Teaching

Archived Teaching Schedule. Please refer to current Teaching Shedule.

BIO4721 Introduction to Pattern Recognition and Machine Learning