Machine Learning, Data Science, Clustering, Classification, Algorithms.
center of the nearest mean cluster points like in the picture on the right. Then we iterate the process multiple times until we got the k-initialization points to the correct cluster (convergence) just like the picture below. K-means are very sensitive to outliers. You can imagine the update