Python | Machine Learning | Flask | AWS | Docker •Built an end-to-end Machine Learning pipeline to predict vehicle insurance outcomes using structured customer data. •Implemented data ingestion, data validation, preprocessing, feature engineering, and model training modules following MLOps best practices. •Trained and evaluated multiple ML models and selected the best-performing model based on evaluation metrics. •Developed a Flask-based web application for real-time predictions. •Containerized the application using Docker and deployed it on AWS for scalable access. •Designed modular, production-ready code with logging, exception handling, and configuration management