Loan eligibility prediction.

In this project, I analyzed data from a financial institution provided by Kaggle and trained five machine learning algorithms: random forest, support vector machine, logistic regression, decision tree, and XGBOOST, with xgboost coming out on top with a training score of 99% and a test score of 90%. The goal of the project was to forecast which bank customers would be qualified for the loan based on the independent features and the goal was to qualify or not.