SmartPremium is an end-to-end machine learning project that predicts insurance premium costs based on customer characteristics and policy details. This project demonstrates the complete data science lifecycle from data exploration to deploying a production-ready web application.
- Optimize premium pricing based on risk factors
- Assess risk for loan approvals tied to insurance policies
- Estimate future healthcare costs for patients
- Provide real-time insurance quotes through data-driven predictions
- Python - Core programming language
- Pandas/NumPy - Data manipulation and processing
- Scikit-Learn - Machine learning models and preprocessing
- XGBoost - Advanced gradient boosting model
- MLflow - Experiment tracking and model management
- Streamlit - Web application deployment
- Joblib - Model serialization and storage
- git clone https://github.com/keshavjatt/SmartPremium-Insurance.git
- cd SmartPremium-Insurance
- pip install -r requirements.txt
- python -m notebook notebooks/eda_preprocessing.ipynb
- python src/train_model.py
- streamlit run streamlit_app/app.py