This project was completed as part of the Web Development Fundamentals course at Sprints.

This project analyzes and predicts heart disease risks using machine learning. It covers the entire workflow from data preprocessing and dimensionality reduction (PCA) to training and evaluating various classification models (Logistic Regression, Decision Trees, Random Forest, SVM) and exploring unsupervised clustering methods.