πŸ—“οΈ Week 08 - Clustering

Theme: Unsupervised Learning

Author

Dr. Ghita Berrada

Note

The lecture notebook was updated:

  • images that didn’t 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.

πŸ‘©πŸ»β€πŸ« Lecture Material

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Download the notebook containing the full lecture Markdown: