You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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.
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.
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.
This project focuses on predicting loan approval for LoanTap’s personal loans using Logistic Regression. It covers EDA, feature engineering, and model evaluation, including classification metrics, ROC-AUC and precision-recall analysis. The study highlights key factors affecting creditworthiness to guide better lending and minimize default risk.
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 Prediction App using Python, Scikit-learn & Streamlit — includes full EDA, feature engineering, model training, and deployment as an interactive web app.