K-Means Clustering (Unsupervised Learning)

1. The Problem It Solves In many real-world problems, we don't have labeled data. We may have thousands of customers, products, or transactions, but no information about which ones belong together. For example: Which customers behave similarly? Which products attract similar buyers? Which users are likely to become power users? Which stores have similar purchasing patterns? K-Means Clustering solves this problem by automatically grouping similar data points together based on their…