Day 21: K-means
Very easy, yet very power technique used in unsupervised learning is k-means clustering.
K-means first chooses some random clusters. Then assigns each point to the nearest cluster using L2 measure and computes a new cluster centre as mean of all the points inside. These two steps are repeated until convergence.

EX: 1000 random points