Cardiovascular Disease Prediction (ML Project)

This project applies machine learning to predict the presence of cardiovascular disease using real-world clinical and lifestyle data. It compares Logistic Regression and Random Forest models.

Dataset

• Source: Kaggle - Sulianova
• Records: 70,000
• Features: Age, BP, cholesterol, glucose, lifestyle habits
• Target: cardio — 0 = no disease, 1 = disease

Models Applied

• Logistic Regression
• Random Forest Classifier

Project Presentation YouTube video link: https://youtu.be/M_RXO1uTLu4

Author

• Name: E.P.M.T.S. EKANAYAKE
• ID: IT21171406
• Email: [email protected]