Clustering with k-Means
So far we had answers to learn from (supervised learning). With unsupervised learning there are no labels and the model looks for structure on its own. k-means groups points into k clusters around centres. The cluster numbers are arbitrary (0 and 1 could be swapped), so look at the groups, not the numbers.
Examplepython
Quick check
What is different about unsupervised learning?
Your turn: write the code
Cluster the points into 3 groups and print the sorted group sizes.
Finish the quick check (and any code exercise) to complete this lesson, or mark it done yourself.
Tip: use the left and right arrow keys to move between lessons.