Heart Disease Predictor

A machine learning web app that predicts whether a patient has heart disease based on their medical details.

Built as Project 1 of a 4-project Machine Learning series using the Zero to Mastery ML course as a learning foundation.

• Takes 13 patient health inputs (age, cholesterol, blood pressure, etc.)
• Uses a trained Random Forest Classifier to predict heart disease
• Shows the result with a confidence percentage
• Green banner = No heart disease detected
• Red banner = Heart disease detected

pip install flask scikit-learn pandas numpy joblib

python3 train_model.py

python3 app.py

http://127.0.0.1:5000

project1-heart-disease/
├── train_model.py       # Downloads data, trains and saves the model
├── app.py               # Flask web server
├── model.joblib         # Saved trained model (generated after training)
├── templates/
│   └── index.html       # Web page with input form and result
└── static/
    └── style.css        # Styling

Heart Disease Dataset from the Zero to Mastery ML course (originally from UCI Machine Learning Repository).

This tool is for educational purposes only. Always consult a qualified medical professional for health decisions.