Heart Disease Prediction App

Heart Disease Prediction App

Developed a Machine Learning web application to predict the likelihood of heart disease based on patient medical data.

Collected and preprocessed medical dataset

Performed data cleaning and feature selection

Applied feature scaling and encoding techniques

Trained classification models (e.g., Logistic Regression / Random Forest)

Evaluated performance using Accuracy, Precision, Recall, and F1-score

Optimized the model using hyperparameter tuning

Deployed the application using Streamlit for real-time predictions

The app allows users to input medical attributes (such as age, cholesterol level, blood pressure, etc.) and instantly receive a prediction result.