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.
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.
Built a Logistic Regression model in R to predict housing loan approvals using financial and demographic data. Performed data preprocessing, feature engineering, and model evaluation using ROC curve and confusion matrix. Achieved ~74% accuracy, showcasing the effectiveness of ML in loan decision-making.
This project will approved or reject the loan applications. Public api, data insights and predictive models for loan prediction project are also provided
Add a description, image, and links to the loan-prediction-analysis topic page so that developers can more easily learn about it.
To associate your repository with the loan-prediction-analysis topic, visit your repo's landing page and select "manage topics."