Uusi opinto-opas (sisältäen myös opetusohjelmat) lukuvuodelle 2018-2019 sijaitsee osoitteessa https://opas.peppi.utu.fi . Tältä sivustolta löytyvät enää vanhat opinto-oppaat ja opetusohjelmat.

The new study guide (incl. teaching schedules) for academic year 2018-2019 can be found at https://studyguide.utu.fi. This site contains only previous years' guides.

x !
Arkistoitu opetussuunnitelma 2016–2018
Selaamasi opetussuunnitelma ei ole enää voimassa. Tarkista tiedot voimassa olevasta opetussuunnitelmasta.
Opinto-oppaat » Matemaattis-luonnontieteellinen tiedekunta » Tulevaisuuden teknologioiden laitos » Koneoppiminen ja algoritmiikka
TKO_3120 Machine Learning and Pattern Recognition 5 op
Organised by
Computer Science
Preceding studies

Learning outcomes

The course gives an overview of many machine learning and pattern recognition methods which can be used to build models and systems based on observed data. After the course students should understand the main principles of machine learning and pattern recognition methods and steps needed for applying them in real applications. The student especially learns the core concepts of overfitting and underfitting and is able to find a suitable balance between these extremes in a given problem at hand.


This course covers the main theories, techniques, and algorithms in machine learning and pattern recognition, starting with simple topics such as linear regression/classification and ending up with more advanced topics such as artificial neural networks and model complexity selection and performance estimation. For pattern recognition most popular feature extraction techniques are introduced and Bayesian decision theory is studied. Both main unsupervised and supervised learning techniques are considered with emphasize on how, why and when they work.

Teaching methods

Teaching method Contact Online
Lectures 28 h 0 h

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Written exam
  • In English
Project / practical work
  • In English


Numeric 0-5.

Study materials

Marsland S., Machine Learning: An Algorithmic Perspective,Chapman & Hall/CRC 2009

Theodoridis S. and Koutroumbas K., Pattern Recognition, 4thedition, Elsevier, 2009

Belongs to following study modules

Tulevaisuuden teknologioiden laitos
Tulevaisuuden teknologioiden laitos
Biokemian laitos
Biokemian laitos
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Implementation details are unavailable.
Tulevaisuuden teknologioiden laitos
MDP in Bioinformatics
MDP in Embedded Computing
MDP in Digital Health and Life Sciences (Tech.)