A decision-safety lab for loan approval: trains a baseline classifier, calibrates probabilities (ECE/Brier), sweeps confidence thresholds to build a coverage, quality frontier and outputs a defensible abstention policy (auto-decide vs review). Includes a Streamlit dashboard for report cards, triage UI, and data quality checks.

This is a Loan Approval Prediction Web App built with FastAPI (Backend) and HTML, CSS, JavaScript (Frontend). It predicts whether a loan application will be approved or not approved based on user input.

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.

Loan Approval using Random Forest Algorithm

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 classification using Apache Spark and Big Data analytics with Logistic Regression and Random Forest.

Predict loan approval from applicant data using scikit-learn. Includes EDA, training pipeline, and a Streamlit demo app.

Proof of concept unbiased loan calculator.

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

ai powered loan approval prediction system built using machine learning and streamlit. the project analyzes applicant financial data to predict loan approval probability, generate risk scores, provide model insights, and support data driven credit decision making through an interactive analytics dashboard.

Exploratory Data Analysis (EDA) of Loan Approval dataset using Python — uncovering trends, correlations and approval patterns.

This project is a web-based Loan Disbursement System designed to manage agents, users, loan approvals, EMI calculations, commission management, and report generation. The system automatically calculates daily EMI based on a fixed 10% interest rate for 30 days, even if the loan tenure is more than 30 days.

Analyze a loan data approval dataset

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.

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.

A Cryptocurrency based on Cryptonote Technology that can easily run on your WordPress website, and designed to give you financial freedom