A web app built from a ML model for predicting loan eligibility using a Random Forest model. Built by Zuck30 from Tanzania.

Quick Links

• 🔭 Predicts loan eligibility for students.
• 👨‍💻 Built with React and FastAPI for a modern, user friendly experience.
• 📊 Provides real time predictions with probability scores.

Deployment

This project is deployed using a decoupled architecture:

• Backend (FastAPI): Hosted on Render.
• Frontend (React): Hosted on Netlify.

You can deploy your own instance by following the instructions in the render.yaml and netlify.toml files.

Skills & Technologies

Frontend & Backend

Tools

Project Overview

Loan eligibility is a website designed to help Tanzanian students assess their eligibility for loans. Users input details like citizenship, academic performance, and family income, and a pre trained Random Forest model predicts eligibility with a confidence score.

• Intuitive Interface: React-powered form for easy input.
• Real Time Predictions: Instant results with "Eligible" or "Not Eligible" status.
• Probability Scores: Shows confidence in the prediction.
• Tanzanian Focus: Tailored for Tanzania use case

Quick Start

Prerequisites

• Python 3.7+
• Node.js and npm
• pip (Python package installer)

Installation

1. Clone the repository:

   git clone https://github.com/zuck30/loan-eligibility.git
   cd loan-eligibility

2. Backend Setup:

   # Create a virtual environment
   python -m venv venv
   # Activate it
   # Windows: .\\venv\\Scripts\\activate
   # macOS/Linux: source venv/bin/activate
   # Install dependencies
   pip install -r api/requirements.txt

3. Frontend Setup:

   cd frontend
   npm install
   cd ..

Local Development

To run the application locally, you will need to run the backend and frontend servers in separate terminals.

1. Run the Backend Server:

# From the project root
uvicorn api.main:app --reload

The backend server will be running at http://localhost:8000.

2. Run the Frontend Server:

# From the project root, in a new terminal
cd frontend
npm run dev

The frontend development server will be running at http://localhost:5173. Open this URL in your browser to use the application. The frontend is configured to proxy API requests to the backend server running on port 8000.

☕️ Support the Project

📄 License

This project is licensed under the MIT License, see the LICENSE file for details.

📞 Support

For questions or issues, open a GitHub issue or contact mwalyangashadrack@gmail.com.