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It is project on Heart Attack Prediction Model based on Random Forest Algorithm which predicts the percent of a person is likely to have a heart attack in the near future.

An end-to-end machine learning project that predicts the risk of heart attack using clinical patient data. This project focuses on building a reliable, interpretable, and healthcare-aware ML pipeline, with special emphasis on minimizing false negatives. This repository contains my individual contribution (KNN implementation) for the group project.