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evidently

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Production-grade MLOps pipeline for image classification. EfficientNet-B0 trained on 14,000 real images (86.85% accuracy) with FastAPI serving, A/B testing, MLflow model registry, drift detection, and GitHub Actions CI/CD. Deployed on Railway. Built for Adobe ML Engineer application.

  • Updated May 31, 2026
  • Python

Production MLOps pipeline for Paris bike traffic prediction. Airflow orchestration, MLflow tracking (Cloud SQL), FastAPI deployment. Features: automated ingestion, drift detection, champion/challenger models, Prometheus+Grafana monitoring, Discord alerts. 15 Docker services locally.

  • Updated Nov 7, 2025
  • Python

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