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Vehicle Insurance

End-to-End MLOps Pipeline for Vehicle Insurance Prediction

Overview

This project demonstrates a full machine learning operations (MLOps) pipeline that handles vehicle insurance data from data ingestion to model deployment. The goal is to build a scalable, automated system that can manage real-world ML workflows using modern tools and cloud services. It integrates data processing, model training, validation, and CI/CD to simulate a real production environment.

My Role & Contributions

Tech Stack

Python Pandas FastAPI Scikit-learn MongoDB AWS Docker Matplotlib Docker

Implementation Details

Swagger UI 1 Swagger UI 1 Swagger UI 1

Results & Impact

View on GitHub