Title: Early Heart Attack Risk Prediction Web App with Streamlit

Description:

This project implements a web application using Streamlit to predict the potential risk of a heart attack based on user-provided information. The underlying machine learning model is trained on a dataset of relevant health factors. Getting Started:

Running the App:

Start the Streamlit Server:
Bash

streamlit run app.py

Usage:

The web app provides a user interface where you can input your health data relevant to heart attack risk assessment (specify the specific features in the README based on your model). The app will then use the trained machine learning model to predict the heart attack risk and display the results.

Further Development:

Enhance the user interface for a more interactive experience. Integrate advanced visualization techniques to present results. Deploy the app on a cloud platform like Heroku or AWS for wider accessibility.

Disclaimer:

This application is for informational purposes only and should not be used as a sole basis for medical diagnosis or treatment. Always consult a healthcare professional for any health concerns.

Contributing (Optional):

If you'd like to contribute to this project, please fork the repository and submit pull requests with your improvements or bug fixes.