Project Overview This project aims to perform customer segmentation on a dataset of credit card users using various clustering techniques. The goal is to identify distinct customer groups based on ...

Built with Python and Streamlit, it covers every step from data loading and pre‑processing to clustering (using K‑Means and DBSCAN) and dimensionality reduction (using PCA and t-SNE). Detailed ...

This study introduces a data-driven approach to customer segmentation using clustering algorithms like K-Means, DBSCAN, hierarchical clustering, and PCA. Customers are segmented based on purchasing ...