Loan-Approval-Prediction-System

Project Description This project is a Machine Learning-based system that predicts whether a loan application will be approved or rejected based on applicant data such as income, loan amount, and other financial features. It includes a trained classification model, a full preprocessing pipeline, and an interactive web application built using Streamlit. Key Features Predict loan approval status (Approved / Rejected) Display prediction probabilities Data preprocessing: Outlier handling (IQR) Categorical encoding Log transformation Feature scaling (StandardScaler) Interactive and user-friendly UI Machine Learning Workflow Data Loading Data Preprocessing Feature Engineering Model Training & Selection Model Saving (.pkl) Deployment using Streamlit Technologies Used Python Pandas & NumPy Scikit-learn Streamlit Joblib