Heart Disease Prediction ML Model

Developed a full machine learning pipeline to predict heart disease using the UCI dataset, including

preprocessing, feature selection, and PCA, with both supervised (Logistic Regression, Random Forest, SVM)

and unsupervised models. Optimized model performance through hyperparameter tuning and built a Streamlit

web UI for real-time predictions and visualization. This project was part of the graduation requirements for the

Sprints Machine Learning certificate.