✅ Week 09 Lab - Solutions

Theme: Clustering and introduction to dimensionality reduction

This week in the lab, you explored the World Values Survey dataset further to try and venture into the unsupervised learning world (in practical terms) for the first time.
You discovered one of the most popular dimensionality reduction techniques, which we’ll revisit in this week’s lecture: principal component analysis or PCA for short.
You were also able to put in practice some of the clustering knowledge you learned about last week (k-means and elbow technique) and were introduced to a new clustering technique we’ll talk more about during this week’s lecture i.e DBSCAN.

You can download the .qmd file below to run the code for this week’s lab for yourselves.