Machine Learning project that predicts lifestyle-related health risks using data analysis and predictive modeling. Built an end-to-end ML pipeline including preprocessing, feature engineering, EDA, and models (regression, classification, clustering) using Python, Pandas, NumPy, and Scikit-learn.