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End-to-end machine learning project for multiclass heart disease prediction using the UCI Heart Disease dataset. Includes data exploration, EDA, leakage-safe preprocessing, training and evaluation of 22 ML models, model comparison, visualizations, and a reusable final prediction pipeline.