---
license: mit
---

# Clustering Algorithms for Customer Segmentation

This repository hosts a project on customer segmentation using various clustering algorithms. It includes the code, a synthetic dataset, trained models, and visualizations.

## Project Overview

This project implements and compares the following clustering algorithms for customer segmentation:
- K-Means
- Hierarchical Clustering
- DBSCAN
- Gaussian Mixture Models (GMM)

The goal is to identify distinct customer groups based on their age and income.

## Repository Contents

- `implementation.ipynb`: The main Jupyter notebook with the complete analysis.
- `data/customer_data.csv`: The synthetic dataset used for clustering.
- `models/`: Contains the saved models for each algorithm and the data scaler.
- `results/`: Contains detailed analysis and comparison of the algorithms.
- `visualizations/`: Includes plots for cluster visualization and analysis.

## How to Use

You can use the trained models and the dataset from this repository for your own analysis. To get started, you can clone the repository and explore the `implementation.ipynb` notebook.

```bash
# Clone the repository
git clone https://huggingface.co/karthik-2905/ClusteringAlgorithms
```

## License

This project is licensed under the MIT License.