Machine Learning implementation for predicting credit default status in the microfinance and MSME (Micro, Small, and Medium Enterprises) sector in Indonesia

End-to-end credit risk prediction system using machine learning, featuring data preprocessing, model tuning, evaluation, and a deployed Streamlit app.

A robust machine learning pipeline using XGBoost to predict loan default risk with high precision.