ποΈ Week 08 - Clustering
Theme: Unsupervised Learning
Note
The lecture notebook was updated:
- images that didnβt render were fixed
- unnecessary libraries were removed and additional install instructions added
- a small implementation section on k-means++ and k-medoid was added
- a few references (articles on k-medoid and DBSCAN) were added
Welcome to the eighth week of this course!
This week, we turn our sights to another family of unsupervised learning techniques: clustering. We learn about what clustering is, when it is used and discover some of the most representive clustering algorithms i.e k-means and DBSCAN.
Your first summative is due this week on November 21st at 5pm.
π©π»βπ« Lecture Material
π₯ Looking for lecture recordings? You can only find those on Moodle, typically a day after the lecture. If you canβt find the recordings, please contact π§ .
Download the notebook containing the full lecture Markdown: