Loan Approval Application

Deployed link: https://loan-approval-app-facb8c5d72fa.herokuapp.com/

This app was made as the final assignment of DPhi's Online Machine Learning Bootcamp. The objective of this Machine Learning project is to build a model and web application that the bank can use to classify if a user can be granted a loan or not.

Endpoints

1. /home: Home page
2. /prediction: Prediction form
3. /result: API
   • Return: [pred_prob, pred_class]
   • See guide/API_Example.ipynb for minimal example

Project Structure

• Folders:

  • dev: development scripts
  • guide: notebook for usage examples
  • models: pickled pre-trained model (scikit-learn pipeline)
  • static: css files
  • template: html files

• Application Files:

  • app.py: main application
  • forms.py: wtforms class

• Deployment Files:

  • requirements.txt: package dependencies
  • runtime.txt: Python version
  • Procfile: commands for app's dynos on Heroku

Dependencies

The app is built using Python 3.12.1, with the following dependencies:

• Flask: web framework
• Flask-WTF: forms validation
• pandas: data analysis
• scikit-learn: model pipeline
• gunicorn: HTTP server

List of dependencies and its version can be found on requirements.txt.

References

• DPhi Datathon 54
• Bootstrap v5.0
• Corey Schafer's Code Snippets

Future Improvement Ideas

• Improve classifier performance
• Create new page for batch prediction, using upload and download file
• Create new page for explainable results, using LIME or SHAP