Mall Customer Segmentation using K-Means Algorithm

This project demonstrates the use of K-Means clustering on two popular datasets: the Iris dataset and the Mall Customers dataset. The goal is to visualize the clustering process and group similar data points, showcasing the practical application of K-Means in real-world data segmentation.

Repository for various clustering projects including mall customer segmentation and more. Explore data analysis and clustering techniques

Mall customer segmentation using K Means Clustering

A mall customer segmentation machine learning model categorizes customers based on their behaviors and preferences, enabling businesses to tailor marketing strategies and optimize operations for improved customer satisfaction and business growth.

Customer Segmentation using KMeans algorithm on Mall_Customers Dataset.

mall cusomer segmenation using usupervised ML (dbscan, k-cmean, fcmean)

This project aims to perform customer segmentation on a Mall customer dataset using the K-Means clustering algorithm. The goal of this project is to cluster the customers based on their purchasing behavior and demographic characteristics.