Mål og innhald
The course introduces Machine Learning, with a view towards data analysis applications. Topics covered are supervised learning (classification and regression) with deep learning, unsupervised learning including clustering, and reinforcement learning.
A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
- 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
- can analyze and design machine learning solutions for data analysis applications
Krav til forkunnskapar
INFO132 or equivalent. Basic understanding of programming and algorithms.
INF264 (10 sp)
Krav til studierett
Emnet er ope for studentar med studierett på UiB. Emnet har 200 studieplassar. Studentar som har emnet som obligatorisk i studieplanen vil ha prioritet.
Arbeids- og undervisningsformer
Lectures, seminars and data labs, normally 2 + 2 hours per week for 12-15 weeks.
Participation: compulsory attendance at labs (at least 75%).
Approved compulsory requirements are valid for the two following semesters.
- 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) - multiple choice exam
Hjelpemiddel til eksamen
All written material in paper form is allowed on the exam.
Assessment only in teaching semester.
The reading list will be ready before 1 June for the autumn semester and 1 Decemeber for the spring semester.
Alle emne blir evaluert i tråd med UiBs kvalitetssystem for utdanning.
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
The Department of Information Science and Media Studies at the Faculty of Social Sciences has the administrative responsibility for the course
Telephone 55 58 90 00