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3️⃣ Regression Project (REGRESSION_PROJECT)

# 📈 Regression Project - Car Insurance Charges

This project uses **regression models** to predict **insurance charges** based on user information (age, BMI, smoking status, region, etc.).

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## 📊 Dataset
- **Dataset**: `insurance.csv` (provided in project).  
- **Features**:  
  - Age  
  - BMI  
  - Children  
  - Sex  
  - Smoker  
  - Region  

- **Target**: Insurance Charges

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## 🧠 Machine Learning Models Used
- Linear Regression  
- Polynomial Regression  
- Decision Tree Regressor  
- Random Forest Regressor  
- Support Vector Regressor (SVR)  

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## ✅ Best Model
- **Random Forest Regressor** gave the best accuracy.  
- Model & preprocessing pipeline saved as:
  - `best_model.pkl`
  - `insurance_scaler.pkl`

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## 🚀 Features
- Predict insurance cost for new users.  
- Encodes categorical variables (sex, smoker, region).  
- Scales numeric features.  

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## ▶️ How to Run
```bash
# Clone repo
git clone https://github.com/talha37000/Regression-Project.git
cd Regression-Project

# Open Notebook
jupyter notebook REGRESSION_PROJECT.ipynb

📌 Future Improvements


Add Tkinter-based prediction GUI.

Deploy as a Flask/Django web app.

Add cross-validation & hyperparameter tuning.

👤 Author

Muhammad Talha Mubeen
🎓 BSCS - Batch 2k21
📧 [muhammadtalhamubeen37@gmail.com]