In this project I have picked up a simple png image and compressed it using K-means. This project was a part of my Unsupervised Machine Learning Course by Andrew NG.
- Concretely, you are given a training set {x(1), x(2)..... x(m)} and you want to group the data into a few cohesive “clusters”.
K-means is an iterative procedure that
- Starts by guessing the initial centroids, and then
- Refines this guess by
- Repeatedly assigning examples to their closest centroids, and then
- Recomputing the centroids based on the assignments.