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Laveregradsemne

Machine Learning

Hovedinnhold

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 75%).

Approved compulsory requirements are valid for the two following semesters.

Update: In the spring semester 2021, the requirement to attend 75% of the seminars will not apply due to the corona situation. However, it is highly recommended that students attend as much as possible.

Vurderingsformer

4 hour written exam.

Update spring 2021: As part of the measures to limit the risk of corona infection the form of assessment will be:

  • Group assignment where students demonstrate their ability to analyze and design machine learning solutions (30% of grade)
  • 2 hour digital home exam (70% of grade)

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).

Emneevaluering

Alle emne blir evaluert i tråd med UiBs kvalitetssystem for utdanning.

Kontakt

studieveileder@ifi.uib.no

Telephone 55 58 90 00

Eksamensinformasjon

  • Vurderingsordning: Gruppeoppgave og heimeeksamen

    Trekkfrist
    09.09.2021
    • Eksamensdel: Gruppeoppgave

      Eksamenssystem
      Inspera
      Digital eksamen
    • Eksamensdel: Heimeeksamen

      Oppgave utleveres
      23.09.2021, 09:00
      Innleveringsfrist
      23.09.2021, 11:00
      Eksamenssystem
      Inspera
      Digital eksamen