Unsupervised learning: K-means clustering, hierarchical clustering, principal components
Introduction to reinforcement learning
Real-world applications of machine learning (e.g. self-driving cars, medical imaging, natural language processing, etc.)
Undervisnings- og læringsformer
The course is organized with a combination of lectures, assignments, paper studies, labs, and report writing. The tasks are done individually or in small groups with group supervision. The workload for the average student is approximately 135 hours.
Eksamen
3 hours written exam (50%). Portfolio assessment (50%). Information about the content of the portfolio will be given in Canvas at the start of the semester for each seminar. Graded assessment.
Studentevaluering
The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.