Use-Cases of K-Means Clustering

In this blog, first of all we will see what is K-Means Clustering Algorithm and then discuss about some of it's Industry use-cases. Unsupervised learning is a type of machine learning in which models are trained using unlabeled dataset and are allowed to act on that data without any supervision. Unsupervised learning cannot be directly applied to a regression or classification problem because unlike supervised learning, we have the input data but no corresponding output data. The goal of unsupervised learning is to find the underlying structure of dataset, group that data according to similarities, and represent that dataset in a compressed format. K-Means Clustering is an Unsupervised Learning algorithm, which groups the unlabeled dataset into different clusters.