This project analyzes a heart disease dataset to identify trends and insights related to heart disease risk factors. It involves data preprocessing, exploratory data analysis (EDA), visualization, and machine learning techniques to predict the presence of heart disease based on patient data.
File: heart_disease.csv Description: The dataset contains medical attributes of patients, such as age, cholesterol levels, blood pressure, and more, with a target variable indicating the presence of heart disease.
Age , Sex , Chest Pain Type , Resting Blood Pressure , Cholesterol , Fasting Blood Sugar , Resting ECG , Maximum Heart Rate , Exercise-Induced Angina , ST Depression , Slope of Peak Exercise , Number of Major Vessels , Thalassemia , Target (Heart Disease: 1 = Present, 0 = Absent)