Customer Segmentation in Retail using K-Means Clustering

This project applies K-Means clustering to segment retail customers based on their shopping habits, product preferences, and spending patterns. By clustering customers, businesses can identify high-value customers, target promotions more effectively, and improve overall sales strategies. The project includes data preprocessing, feature selection, and the implementation of the K-Means algorithm.