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This project is a web application for predicting loan approval status based on various financial and personal attributes. It uses a machine learning model that I trained on historical loan data to make predictions. I built the web application using Flask for the web framework, SQLite for the database, and the pre-trained model saved with joblib.

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Tynoee/Loan-Approval-Prediction

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Loan-Approval-Prediction

This project is a web application for predicting loan approval status based on various financial and personal attributes. It uses a machine learning model that I trained on historical loan data to make predictions. I built the web application using Flask for the web framework, SQLite for the database, and the pre-trained model saved with joblib.

The following machine learning models were explored and evaluated for the prediction task:

  • Logistic Regression
  • Decision Tree
  • Random Forest
  • Gradient Boosting
  • Support Vector Machine

Features

  • Predicts loan approval status based on user input.
  • Utilizes a machine learning model trained on historical loan data.
  • Provides a user-friendly interface for inputting loan application details.
  • Stores client information and prediction results in a SQLite database.

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More Information

Please go through Loan_Prediction for more information.

About

This project is a web application for predicting loan approval status based on various financial and personal attributes. It uses a machine learning model that I trained on historical loan data to make predictions. I built the web application using Flask for the web framework, SQLite for the database, and the pre-trained model saved with joblib.

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