In recent years, predicting heart disease has grown to be one of the most challenging problems in medicine. About one
person dies from heart disease every minute in the modern era. In the healthcare industry, machine learning is crucial for
handling massive amounts of data. Since predicting cardiac disease is a complicated procedure, it is necessary to automate the
process in order to minimize risks and forewarn patients. The heart disease dataset from the machine learning repository is used
in this study. By implementing KNN AND SVM, RF the suggested study predicts the risk of heart disease and categorizes the
patient's risk level.
