Amazon SageMaker Solution for explaining credit decisions.

A Classification Problem which predicts if a loan will get approved or not.

This repo contains my loan approval prediction project in Python.

[Project repo] Improving business with a credit risk model

This project automates bank credit risk assessment using AI and machine learning models to predict loan defaults. It streamlines the credit process with predictive analytics, model evaluation, explainability (SHAP), and deployment readiness.

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

Python Data Analytics, Machine Learning & Natural Language Processing

In this Notebook , We are going to solve the Loan Approval Prediction.This is a Classification problem in which we need to classify whether the loan will be approved or not.

Should you get a loan? Will you pay on time?

Loan eligibility prediction in Lasiandra Finance Inc. (LFI) using SAS studio.

Business Intelligence( BI) & Tableau

What's up This project was mainly training my self on training ML models 🤖 and also to train on doing EDA 📜 to get the acceptance of the loan.

Loan eligibility prediction with Logistic Regression

In this project, I analyzed the prosper load data, studied the trends and concluded that monthly income, loan amount and borrower's rate significantly affect the prosper rating and a good predictors of delinquency.

It is a classification problem where we have to predict whether a loan would be approved or not.

I’d be walking us through Loan prediction using some selected Machine Learning Algorithms.

This project will approved or reject the loan applications. Public api, data insights and predictive models for loan prediction project are also provided

In this data science project, we will predict borrowers chance of defaulting on loans by building a default prediction model.

This project demonstrates a machine learning approach to predict loan approvals using a Decision Tree Classifier.

No description provided.

Loan Prediction using machine learning

Minimization of risk and maximization of profit on behalf of the bank

This a practice project for Classification model with different models like Logistic Regression, Decision Tree Classifier, Random Forest Classifier and Xgboost Classifier. At the end, Logistic Regression gave the best result.

Machine Learning

This repo is for derived from a competition from analytics vidhya for predicting loan using the data given.

We find which attributes matter the most for loan decisions using neural attention. NIPS 2019 workshop

No description provided.

An end-to-end machine learning project that predicts loan approval status based on customer profiles. Developed with Python and scikit-learn, it encompasses data preprocessing, feature scaling, model training, evaluation, and hyperparameter tuning. The project also features a user-friendly GUI for seamless user interaction.

Loan Approval Prediction using Logistic Regression, Decision Tree, Random Forest and XGBoost

Suppose you work for a consumer finance company which specialises in lending various types of loans to urban customers. You have to use EDA to analyse the patterns present in the data. This will ensure that the applicants capable of repaying the loan are not rejected.