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Laveregradsemne

Machine Learning

Undervisningssemester

Spring

Mål og innhald

The course introduces Machine Learning, with a view towards data analysis applications. Topics covered are supervised learning (classification and regression), unsupervised learning including clustering, decision tree learning, Bayesian learning, and working with textual data.

Læringsutbyte

A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The candidate

  • has theoretical knowledge about the principles of machine learning
  • has a basic understanding of the contemporary machine learning algorithms
  • has a broad knowledge about the use of machine learning in data analysis, its advantages and limitations

Skills

The candidate

  • can analyze and design machine learning solutions for data analysis applications

Krav til forkunnskapar

INFO132 or equivalent. Basic understanding of programming and algorithms.

Studiepoengsreduksjon

INF264 (10 sp)

Krav til studierett

The course is open to all students at the University of Bergen.

Arbeids- og undervisningsformer

Lectures, seminars and data labs, normally 2 + 2 hours per week for 12-15 weeks.

Obligatorisk undervisningsaktivitet

  • Compulsory assignments, which have to be approved in the teaching semester.
  • Participation: compulsory attendance at labs (at least 80%).

Approved compulsory requirements are valid for the two following semesters.

Vurderingsformer

4 hour written exam.

Hjelpemiddel til eksamen

All written material in paper form is allowed on the exam.

Karakterskala

A-F

Vurderingssemester

Assessment in teaching semester and in the following semester (for the students who have valid obligatory assignments and attendance).

Kontakt

Kontaktinformasjon

studieveileder@ifi.uib.no

Telephone 55 58 90 00

Eksamensinformasjon

  • Klokkeslett for oppstart av skoleeksamen kan endre seg fra kl 09.00 til 15.00 eller vice versa inntil 14 dager før eksamen. Eksamenslokale publiseres 14 dager før eksamen. Kandidatene finner sin egen romplassering på Studentweb 3 dager før eksamen.

  • Vurderingsordning: Skuleeksamen

    Dato
    25.09.2019, 09:00
    Varigheit
    4 timer
    Trekkfrist
    11.09.2019
    Eksamenssystem
    Inspera
    Digital eksamen
    Sted