Customer Segmentation using K-Means Clustering

This project focuses on customer segmentation using machine learning techniques to group customers based on their behavior and purchasing patterns.

The workflow includes:

- Data preprocessing and cleaning

- Feature scaling and transformation

- Clustering using K-Means algorithm

- Determining optimal clusters using Elbow Method

- Visualizing clusters using PCA

Tools & Technologies:

Python, Pandas, Scikit-learn, Matplotlib, Seaborn

Key Results:

- Clear customer segmentation into distinct groups

- Improved understanding of customer behavior

- Useful insights for targeted marketing strategies

This project demonstrates my ability to extract meaningful patterns from data and support business decision-making.