Learning outcomes

The course introduces the basic methods of neurocomputing and their applications in different problems.

Contents

Methods of neurocomputing and algorithms in conjunction with networks with forward and backward input are examined. Topics include also the supervised and unsupervised learning of neural networks. The examined methods are discussed in the context of application examples such as making various inferences.

Teaching methods

Teaching method	Contact	Online
Lectures	36 h	0 h
Exercises	18 h	0 h

Teaching language

Finnish

Evaluation

Numeric 1-5.

Recommended year of study

3. year spring

Advanced studies, 3rd year, spring semester or later.
The course is not lectured every year.

Study materials

Simon Haykin, Neural Networks: A Comprehensive Foundation, 2. edition, Prentice Hall, 1999.

Belongs to following study modules