About

This Heart Disease Risk Prediction canvas provides a comprehensive machine learning workflow that transforms raw health data into predictive insights. Through rigorous exploratory data analysis, advanced preprocessing, and training of multiple models (Logistic Regression, Random Forest, and Gradient Boosting), the project systematically analyzes heart disease risk factors. The workflow includes detailed feature exploration, categorical and numerical feature engineering, model training, and a thorough evaluation comparing model performances, ultimately demonstrating a robust approach to predicting cardiovascular health risks with over 86% accuracy.