Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide. Early
detection and timely intervention are crucial for preventing adverse outcomes. This research
explores the application of machine learning (ML) techniques for the prediction of
cardiovascular diseases, leveraging a dataset comprising diverse clinical parameters.