🩺 Diabetes Prediction using Support Vector Machine (SVM)

This project uses the PIMA Diabetes Dataset to train a machine learning model that predicts whether a person is diabetic based on health-related attributes.

📌 Overview

The model uses:

• StandardScaler for feature standardization.
• Support Vector Machine (SVM) with a linear kernel for classification.
• Accuracy Score for evaluation.

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📂 Dataset

The dataset is the (https://www.dropbox.com/scl/fi/0uiujtei423te1q4kvrny/diabetes.csv?rlkey=20xvytca6xbio4vsowi2hdj8e&e=1&dl=0), which contains:

• 8 Features (e.g., glucose level, BMI, age, etc.)
• 1 Target: Outcome
  • 0 → Not Diabetic
  • 1 → Diabetic

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🚀 How to Run

1️⃣ Requirements

Make sure you have Python 3.x installed along with the required libraries:

pip install numpy pandas scikit-learn

git clone (https://github.com/riminipa16/-Diabetes-Prediction-using-Machine-Learning-with-Python)
cd Diabetes-Prediction-using-Machine-Learning-with-Python