Loan Approval using Random Forest Algorithm
FoxTrend uses advanced machine learning to provide insightful stock price forecasts and comprehensive company information. The platform also offers additional features, such as car price prediction, loan approval assessment, and housing price estimation.
A Django-based Credit Approval System that intelligently determines loan eligibility and offers real-time insights based on past loan data and customer profiles using PostgreSQL.
Loan Approval Business Process and Web Services parent project
Credit Score Modelling: Perform a Weight of Evidence Logistic Regression Modelling (WoELR) to generate credit scorecard for loan approval.
This project focuses on building a machine learning model to predict the approval status of loan applications based on applicant information. It explores data preprocessing, visualization, feature engineering, and classification modeling.
Predicting personal loan approval using machine learning techniques
A web app built with React and Flask to predict loan approval using machine learning. Evaluates user inputs (income, loan amount, CIBIL score) and provides predictions, probability scores, and feature importance.
Predicts loan approval using demographic and financial data. Includes data cleaning, EDA, feature engineering, and ML models (Logistic Regression, Random Forest). Achieved ~79% accuracy. Full notebook, predictions, and insights documented.
Loan approval prediction means using credit history data of the loan applicants and algorithms to build an intelligent system that can determine loan approvals.
Loan Approval Dashboard using SQL, Python, and Power BI
Loan Approval Prediction using Machine Learning | EDA + Decision Tree, Random Forest & Logistic Regression | Automating loan eligibility for Dream Housing Finance by analyzing customer data and predicting loan approvals.
A Cryptocurrency based on Cryptonote Technology that can easily run on your WordPress website, and designed to give you financial freedom
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