This project applies unsupervised learning to segment credit card customers based on their spending and payment behavior. Using clustering algorithms like K-Means and Agglomerative Clustering, the goal is to identify groups of customers with similar financial activity patterns to help with customer segmentation, marketing, and risk analysis.