Clustering can be considered the most important unsupervised machine learning problem; so, like every other problem of this kind, it deals with finding a structure in a collection of unlabeled data.
A loose definition of clustering could be “the process of organizing objects into groups whose members are similar in some way”.
A cluster is, therefore, a collection of objects which are “similar” between them and are “dissimilar” to the objects belonging to other clusters.

Clustering Algorithms

Learn about the most important clustering algorithms

Advanced Clustering

One fundamental question is: If the data is clusterable, then how to choose the right number of expected clusters (k)?

The elbow method for clustering

Let the machine find the optimal number of clusters from your data