heart_disease_prediction

A heart disease prediction model was built using machine learning with Python. The data was preprocessed and cleaned, feature engineering was performed, and the data was split into training and testing sets. Different machine learning algorithms such as KNN, Decision Tree, Random Forest, and Logistic Regression were used to build the model. The model's performance was evaluated using metrics such as accuracy, precision, recall, and F1 score. Finally, the model was saved for future use.