GitHub - AsadAhmed29/Heart-Attack-Analysis-with-different-Classifiers: The Heart Attack Prediction project uses machine learning to predict heart attack risk based on clinical data. After implementing algorithms like Logistic Regression, SVM, KNN, and Random Forest, the Random Forest model achieved 92% accuracy. Key predictors, such as maximum heart rate and chest pain

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The Heart Attack Prediction project uses machine learning to predict heart attack risk based on clinical data. After implementing algorithms like Logistic Regression, SVM, KNN, and Random Forest, the Random Forest model achieved 92% accuracy. Key predictors, such as maximum heart rate and chest pain