|Kursusnavn (dansk):||Machine Learning |
|Kursusnavn (engelsk):||Machine Learning |
|Semester:||Efterår 2018 |
|Udbydes under:||Bachelor i datavidenskab (b-ds) |
|Omfang i ECTS:||15,00 |
|Min. antal deltagere:||40 |
|Forventet antal deltagere:||0 |
|Maks. antal deltagere:||60 |
|Formelle forudsætninger:||The course is only open to BSc DS third semester. |
|Læringsmål:||After the course, the student should be able to:
- Discuss, clearly explain, and reflect upon central machine learning concepts and algorithms.
- Choose among and make use of the most important machine learning approaches in order to apply (match) them to practical problems.
- Implement abstractly specified machine learning methods in an imperative programming language
- Combine and modify machine learning methods to analyse practical dataset and covey the results.
|Fagligt indhold:||The following subjects will be covered in the course.
- Linear models for regression and classification
- Neural networks
- Kernel methods
- Graphical models
- Mixture Models and EM
- Continuous Latent Variable
- Models for Sequential Data
- Ensemble methods
The first 10 weeks will consist of lectures and exercise sessions. The last 4 weeks will consist of project work.
- Active participation in exercise sessions (details will be given though LearnIT)
- Five peer graded hand-ins. (deadlines are disrubted over the semester, details will be given though LearnIT)
If the mandatory active participation is not approved, an alternative test will be held at the end of the course (see details on LearnIT).
Be aware: The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.
|Eksamensform og -beskrivelse:||D2G Aflevering med mundtlig eksamen der supplerer projekt. Delt ansvar for projekt., (7-scale, external exam)|
The group makes their presentations together and afterwards the students participate in the dialogue individually while the rest of the group is outside the room.
The exam will last 20 min per students.
The groups must consist of 2-3 persons.