Contious to Clustering Methods course.
Teaching consists of (1) Youtube video lectures; (2) exercises. Some of the teaching can be online lectures that will be recorderd. Some of the exercises can be self-examination or direct teacher/student consultation.
Exercises are made at your own time. Minimum of 33% tasks need to be done to pass the course. Deadline for the submissions each week is Tuesday 10:00. All submitted exercises count as one point. To pass the course, you need 33% of the total points. Participating the exercise sessions is obligatory.
Submit your exercises in eLearn (key: "clustering2"): eLearn
Lecturer: Pasi Fränti
Course assistant: Fei Wang
Exercise sessions:Video lectures are available in the same youtube playlist as the lectures of Clustering Methods course: Youtube
Exercises: Tuesday 10-12: Teams
24.3. Overlap + balanced k-means
31.3. Agglomerative clustering + Mumford-Shah
14.4. Branch-and-bound + Stability
21.4. Density-based clustering
28.4. Applications
x.x. Clustering Twitter data
Exercise 1 completed
Exercise 2 completed
Exercise 3 bew!
Exercise 4 new!
Exercise 5 new!
Exercise 6 new!
Exercise 7
Submit your exercises in eLearn (key: "clustering2"): eLearn
Clustering Methods
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