This is a simple loan approval predictor application built using FastAPI and scikit-learn. It predicts whether a loan application will be approved or denied based on input features such as age, income, loan amount, etc.
- Frontend: HTML form with Bootstrap for styling.
- Backend: FastAPI for serving predictions.
- Machine Learning Model: Decision Tree Classifier trained using scikit-learn.
- Data: CSV dataset containing loan application information.
- Clone the repository:
git clone https://github.com/santhosh-vairamuthu/Loan-Approval-Predictor
- Install dependencies:
pip install -r requirements.txt
- Run the FastAPI application:
uvicorn app.main:app --reload
- Open your web browser and go to
http://localhost:8000
to access the loan application form. - Fill out the form with the required information.
- Submit the form to get the loan approval prediction result.
The dataset used for training the model is stored in app/ml/loan_data.csv
. It contains information about loan applications, including age, income, loan amount, credit score, etc.
This project is licensed under the MIT License. See the LICENSE file for details.