Heart Disease Prediction

This project uses machine learning to predict whether a patient is likely to have heart disease, based on clinical features.

Objective

Build a system that can predict if a patient has heart disease. Explore the data, understand the features, and figure out an approach.

Dataset

The dataset contains features like:

• Age, sex, resting blood pressure, cholesterol, fasting blood sugar, etc.
• Target: 0 = No Heart Disease, 1 = Heart Disease

Methodology

• Data Cleaning and Exploration
• Feature Correlation Analysis
• Logistic Regression Model
• Performance Evaluation (Accuracy, Confusion Matrix, Classification Report)

Result

Achieved 86.89% accuracy using logistic regression.

Notebook

All code is in heart_disease_predictor.ipynb

📌 Author

Reha