🩺 Diabetes Prediction using SVM

This project uses a Support Vector Machine (SVM) classifier to predict whether a person is diabetic based on health-related parameters. It includes a Gradio web app for live predictions and saves the model and scaler for deployment.

🚀 Features

• 🔍 SVM model for classification
• 📊 Data standardization with StandardScaler
• ✅ Model evaluation with accuracy score
• 💾 Model saved as model.pkl and scaler.pkl
• 🌐 Gradio web interface for easy predictions

📂 Files

-Dataset.ipynb – Jupyter notebook for data loading, preprocessing, model training, evaluation, and saving .pkl files.

• diabetes.py – Python script version of the notebook for training and saving the model.
• diabetes.csv: Dataset
• model.pkl: Trained SVM model
• scaler.pkl: StandardScaler used for preprocessing
• requirements.txt: List of dependencies

Interface