Heart Disease Classification using Machine Learning

Developed a Machine Learning model to predict the presence of heart disease based on patient medical attributes.

Performed data preprocessing including handling missing values, encoding categorical variables, and feature scaling to enhance model performance.

Trained and evaluated multiple classification models using performance metrics such as accuracy, precision, recall, and F1-score.

The project was implemented using Python with libraries including Pandas, NumPy, and Scikit-learn