We present k-means clustering algorithms: a k-means is its cluster model. The concept is based on spherical clusters that are separable in a way so that the mean value converges towards the cluster center.
After the necessary introduction, Data Mining courses always continue with K-Means; an effective, widely used, all-around clustering algorithm. Before actually running it, we have to define a distance function between data points (for example, Euclidean distance if we want to cluster points in space), and we have to set the number of clusters we want (k).