Aditya-Ramachandran/cardiovascular-disease-detection — reverse-engineered prompt

Build me a simple cardiovascular disease detection project using machine learning. I want a small web app where someone can enter the common health details from the Kaggle cardiovascular disease dataset, like age, gender, blood pressure, cholesterol, glucose, smoking, alcohol use, activity, height, and weight, then get a clear prediction about whether they may be at risk.

Use ensemble learning with the models described in the project idea, Random Forest, KNN, Decision Tree, XGBoost, and a stacked model if it makes sense. Please include basic data cleaning, exploratory charts, model training, accuracy comparison, and a saved prediction flow that the app can use. The app should have a friendly home page, an about page explaining cardiovascular disease in plain language, and a prediction page with a clean form and result message.

Keep the design simple and readable with basic styling. Add any setup notes needed so I can install the requirements and run the app locally. Look up current docs online if you need to.