Loan Application Prediction through machine learning moldes : Logistic Regression, Random Forest, DecisionTree,

Loan Approval Prediction Problem Type Binary Classification Training Accuracy 84% Loan approval prediction is classic problem to learn and apply lots of data analysis techniques to create best classification model. Given with the data set consisting of details of applicants loan and status whether the loan application is approved or not. Basis o…

A simple deep neural network model to predict the approval of personal loan for a person based on features like age, experience, income, locations, family, education, exiting mortgage, credit card etc.

Flask app for predicting loan grant. Model Deployed using Heroku.

This GitHub repository contains a Python script for a machine learning project focused on predicting loan approval using a Support Vector Machine (SVM) classifier.

Developed ML Model to predict whether a loan will be approved or not, based on various parameter, such as Marital Status, Income, etc.

Loan Application Evaluator, using ML approach, Flask and Heroku.

It is a classification Problem where we are supposed to predict whether a loan would be approved or not.

The project aims to predict loan approvals based on various factors, leveraging machine learning models and data pipelines.

Machine Learning Project - Loan Approval Prediction

Loan approval predictive model using classical classifiers.

The project employs Flask-Login for user session management, bcrypt for password hashing, and Flask-Migrate for database migrations. It serves as an example of integrating machine learning functionality within a web application for loan eligibility determination

About Loan Approval Prediction Problem Type Binary Classification Training Accuracy 84% Loan approval prediction is classic problem to learn and apply lots of data analysis techniques to create best classification model. Given with the data set consisting of details of applicants loan and status whether the loan application is approved or not.

Loan Approval Prediction Project