Diabetes_Prediction-ML-Project

This is a Machine Learning project that predicts whether a person is diabetic or not using medical attributes from the Pima Indians Diabetes dataset.

📌 Overview

The project uses a Support Vector Machine (SVM) classifier from scikit-learn to build a prediction model. The dataset is preprocessed with feature scaling (StandardScaler) and evaluated using accuracy score.

🧰 Technologies Used

• Python
• NumPy
• Pandas
• scikit-learn

📁 Dataset

Dataset: Pima Indians Diabetes Dataset
Filename: diabetes.csv

🧪 Steps Performed

1. Data Loading and Exploration using pandas
2. Feature Scaling using StandardScaler
3. Train-Test Split using train_test_split
4. Model Training using sklearn.svm.SVC
5. Model Evaluation using accuracy_score

🚀 How to Run

# 1. Clone the Repository
git clone https://github.com/your-username/Diabetes_Prediction-ML-Project.git
cd Diabetes_Prediction-ML-Project

# 2. Install Dependencies
pip install -r requirements.txt

# If you don’t have a requirements.txt yet, create one:
# pip freeze > requirements.txt
# Or manually install:
# pip install numpy pandas scikit-learn

# 3. Run the Code

# Option A: If you're using a Jupyter Notebook
jupyter notebook
# Then open diabetes_predictor.ipynb and run all cells

# Option B: If you're using a Python script
python diabetes_predictor.py