Heart Disease prediction

Heart Disease Prediction Project Introduction This project aims to develop a machine learning model to predict the likelihood of heart disease based on various health-related features such as age, sex, blood pressure, cholesterol levels, and other relevant attributes.

Data The dataset includes features such as:

Age Sex Chest pain type (4 values) Resting blood pressure Serum cholesterol in mg/dl Fasting blood sugar > 120 mg/dl Resting electrocardiographic results (values 0, 1, 2) Maximum heart rate achieved Exercise-induced angina ST depression induced by exercise relative to rest Slope of the peak exercise ST segment Number of major vessels (0-3) colored by fluoroscopy Thalassemia (3 = normal; 6 = fixed defect; 7 = reversible defect)