This project was developed as a self-study assignment with the primary goal of creating a functional, interactive application for customer segmentation. The application is built using Streamlit and leverages Scikit-learn clustering algorithms. It serves purely educational purposes to demonstrate data preprocessing, model training, and data visualization in a web environment.
Follow these steps to quickly set up and run the Streamlit application on a Linux environment.
- Python 3.8+
- Git
- Clone the Repository
Clone the project files from GitHub to your local machine:
git clone https://github.com/Sam1624/customer_segmentation.git
cd customer_segmentation- Create and Activate Virtual Environment. It's highly recommended to use a Python virtual environment (venv) to isolate dependencies:
python3 -m venv venv
source venv/bin/activate- Install Dependencies
pip3 install -r requirements.txt- Run the application
streamlit run app.pyThis project is licensed under the MIT License. See the LICENSE file for details.