diabetes-prediction-PyCaret-

🌟 Features

1. 🎨 Custom User Interface

   • Clean white background for a professional look.

   • Bold white labels for input fields.

   • Modern blue-styled prediction button.

   • Sliders with black text for better readability.

2. 🩺 Input Form for Health DataUsers can enter health metrics via interactive sliders:

   • Pregnancies 🤰

   • Glucose level 🩸

   • Blood Pressure 💓

   • Skin Thickness 🧬

   • Insulin 💉

   • BMI (Body Mass Index) ⚖️

   • Diabetes Pedigree Function (Genetic Risk) 🧪

   • Age 🎂

3. 🤖 Machine Learning Integration

   • Loads a pre-trained PyCaret classification model (best_diabetes_model).

   • Uses predict_model() to make predictions on user input.

4. 📊 Prediction Results

   • Outputs whether the user is Diabetic 🚨 or Not Diabetic ✅.

   • Displays the confidence percentage of the prediction.

   • Results shown in a clear, color-coded message (st.error for diabetic, st.success for not diabetic).

5. ⚡ Real-time Interaction

   • The app responds instantly when the “🔍 Predict” button is clicked.

   • Users can adjust inputs and immediately get new predictions.

👉 In short:This app is a fast, interactive, and user-friendly diabetes prediction tool powered by Streamlit and PyCaret. It’s useful for demonstrations, educational purposes, and as a base for healthcare-related predictive systems.

click on the image to see more about the project ⬆️