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evidently

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End-to-end platform for training, deploying, and monitoring a churn prediction model—built using MLOps best practices and tools applied from the DataTalksClub MLOps Zoomcamp. Project earned the highest-tier score (top 10 out of 180+ participants) in peer-reviewed project assessment.

  • Updated Aug 13, 2025
  • Jupyter Notebook

This project adopts a modular Python architecture within an MLOps framework to enhance subscription renewal predictions, utilizing FastAPI and MongoDB with AWS integration (S3, ECR, EC2). Docker ensures seamless deployment, and GitHub Actions automate the CI/CD workflows. Evidently AI monitors drift to guarantee predictive accuracy and reliability.

  • Updated Apr 25, 2024
  • Jupyter Notebook

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