This project is a churn prediction and visualization dashboard for a telecommunications company. It aims to predict customer churn and provide insightful visualizations to help the company understand and mitigate churn.
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Features
- Churn Prediction: Uses machine learning to predict the likelihood of a customer leaving.
- Interactive Visualizations: Provides various charts and graphs to visualize customer data and churn predictions.
- User Authentication: Secure login system using JWT.
- Responsive Design: Compatible with both desktop and mobile devices.
- [Demo]
The project is built using a React frontend and a Flask backend.
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Frontend
- React: Handles the user interface and client-side logic.
- Material-UI: Provides a set of React components for faster and easier web development.
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Backend
- Flask: Provides the API endpoints and handles server-side logic.
- SQLAlchemy: Used for ORM (Object Relational Mapping) to interact with the database.
- Redis: Used for caching.
- JWT: Used for secure user authentication.
- Pandas: Utilized for reading the ML model for prediction.
- Scikit-Learn: Utilized for the churn prediction model.
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Database
- PostgreSQL: Stores user data and churn predictions.
- Install packages
yarn
- Run project
yarn start
- Install packages
flask
- Place cmd in server folder
cd server
- Activate virtual env
.\env\scripts\activate.bat
- Run project
flask run
Start the Flask backend server.
Start the React frontend.
Open your browser and navigate to http://localhost:3000 to access the dashboard.
Frontend: React, Material-UI, JavaScript
Backend: Flask, Python, SQLAlchemy, Redis, JWT, Pandas, Scikit-Learn
Database: PostgreSQL
This project is licensed under the MIT License - see the LICENSE file for details.
Name: Abib Fatima
Email: fatima.abib5@gmail.com
GitHub: AbibFatima
_________________________________
Name: Bouzidi Sarra
Email: sarrabzd29@gmail.com
GitHub: sarrabzd29