The objective of this work is to investigate factors affecting borrower rate and loan amount.

Loan status prediction using machine learning and logistic regression involves forecasting whether a loan will be approved or not based on various applicant features and historical data.

This repository showcases efforts to improve the performance of classification models using diverse feature selection techniques. The case study revolves around predicting loan statuses.

This project uses machine learning algorithms to predict the classification of loan status. The dataset is loaded and some transformation is done using SQL for getting a proper dataset with some valid informations.

In this project, we build and train a model to predict if a customer will defer on a particular loan on an imbalanced dataset. We'll build a layered ANN for this and try to make our model better using Hyperparamater Optimization, before exploring Oversampling to make it more accurate.

Code of Loan Status Prediction Project, which we can use to detect the status of a loan. and this is an end-to-end project along with this deployed it on Heroku.

This project uses machine learning algorithms to predict the classification of loan status. The dataset is loaded and some transformation is done using SQL for getting a proper dataset with some valid informations.