What is K-Means?

K-Means Clustering is an unsupervised learning algorithm that is used to solve the clustering problems in machine learning or data science. In this article, I would be giving you a detailed explanation and how this model works. Unsupervised Learning method K-Means Clustering divides the unlabeled dataset into various clusters. K specifies the number of pre-defined clusters that must be produced throughout the process; for example, if K 2, two clusters will be created, and if K 3, three clusters will be created, and so on. It allows us to cluster data into distinct groups and provides a simple technique to determine the categories of groups in an unlabeled dataset without any training. It's a centroid-based approach, which means that each cluster has its own centroid.