This project is a web-based application designed to predict the likelihood of loan approvals. It features:
- A FastAPI backend that handles machine learning predictions.
- A Streamlit frontend that provides a user-friendly interface for making loan predictions.
The application is containerized with Docker for easy deployment and scalability, but you can also run it locally with Python.
- Predict loan approval probabilities using machine learning.
- Interactive web interface for entering loan data and viewing results.
- API endpoint for integrating predictions into other applications.
- Introduction to the project
- Development Documentation
- Deployment and CI/CD Documentation
- API Documentation
You can set up and run this project in two ways: using Docker or installing dependencies manually with Python.
Ensure you have Docker and Docker Compose installed on your machine.
- Clone the repository:
git clone https://github.com/muchai254/loan-prediction cd loan-prediction - Build and run the containers
docker-compose up --build
Ensure you have Python 3.8+ and pip installed.
- Clone the repository:
git clone https://github.com/muchai254/loan-prediction cd loan-prediction - Install dependencies
cd app pip install -r requirements.txt cd server pip install -r requirements.txt
- Start the fastAPI backend
cd server fastapi dev server.py - Start the Streamlit frontend
cd app streamlit run streamlit-app.py
In both installations, the server will run on http://localhost:8000 and frontend at http://localhost:8501
We welcome contributions! Follow the steps below to contribute:
Click the Fork button at the top right of the repository page on GitHub.
git clone https://github.com/muchai254/loan-prediction
cd loan-prediction git checkout -b your-feature-branchPlease do not push changes directly to the master branch. Always use a new branch for your contributions.