How do you choose k for the k-means?

In order to choose k for k-means clustering, we employ the elbow approach. The elbow technique works by applying the k-means clustering algorithm on the data set, where k is the number of clusters.

It is referred to as the sum of the squared distances between each cluster member and its centroid.