Understanding KMeans Clustering for Data Science Beginners

Clustering is an unsupervised learning method whose job is to separate the population or data points into several groups, such that data points in a group are more similar to each other dissimilar to the data points of other groups. It is nothing but a collection of objects based on similarity and dissimilarity between them. KMeans clustering is an Unsupervised Machine Learning algorithm that does the clustering task. In this method, the'n' observations are grouped into'K' clusters based on the distance. The algorithm tries to minimize the within-cluster variance(so that similar observations fall in the same cluster).