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bank-loan-prediction-ml-app
GitHubRepository

bank-loan-prediction-ml-app

A Machine Learning project that predicts loan repayment outcomes through a responsive web application using Python and Scikit-learn.

  • 1 stars
  • 0 forks
  • Jupyter Notebook language
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Published
3 Aug 2026
Updated
7 Sept 2026
AI summary

This repository contains a machine learning project that predicts loan repayment outcomes through a web application. It uses Python and Scikit-learn to train a logistic regression model on historical loan data, and provides a responsive frontend for user interaction.

From the README

💳 LoanSafe Score – Bank Loan Prediction Web App LoanSafe Score is an end-to-end Machine Learning web application that predicts whether a loan applicant is likely to repay or default on a loan based on customer information. The application combines a Python backend with a modern, responsive frontend built using Loveable AI. A Logistic Regression model is trained on historical loan repayment data, evaluated on unseen test data, and used to generate predictions for new applicants. 🔗 Live Demo: https://loan-safe-score.lovable.app 🏠 Web App Home Page --- 📝 Loan Application Form Users can input customer information through an intuitive interface to generate loan repayment...

Skills

  • Jupyter Notebook
  • bank-loan-analysis
  • data-science
  • loan-prediction
  • logistic-regression
  • loveable-ai
  • machine-learning
  • portfolio-project
  • python
  • scikit-learn
  • web-application

More work by Akshat Raghav