Customer Segmentation Project

This project aims to analyze and segment customers using Machine Learning algorithms to understand their behavior and improve marketing strategies.

🚀 Overview

This project is built using Python to analyze customer data and apply the K-Means Clustering algorithm to categorize customers into segments based on their purchasing characteristics.

🛠 Technologies Used

• Python: The core programming language.
• Pandas & NumPy: For data manipulation and analysis.
• Scikit-learn: For implementing machine learning algorithms.
• Streamlit: For creating an interactive project dashboard.

📂 Project Structure

• data/: Contains the dataset used for analysis.
• app.py: The code for the interactive Streamlit interface.
• customer_clustering.py: The code for building and training the model.
• requirements.txt: The dependencies required to run the project.

📊 Results

The model identified [enter number of clusters, e.g., 5] customer segments, which helps in targeting each group with appropriate offers.

💡 How to Run the Project?

1. Clone the repository:

   git clone [https://github.com/alimohmedelsaid26-cell/Customer-Segmentation.git](https://github.com/alimohmedelsaid26-cell/Customer-Segmentation.git)