From Notebook to Production: Building a Robust ML Pipeline with Airflow and CI/CD
From notebook to production: orchestrating an ML pipeline with Apache Airflow, data validation, CI/CD, deployment, and observability.
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Publications Tags : #MLOps
Our Articles
Technical articles, lessons learned, architecture decisions and insights from real projects.
When an ML Improvement Doesn't Survive Validation
Why an apparent ML gain can disappear under more rigorous validation: statistical uncertainty, selection bias, redundancy, and system-level impact.
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Building a Temporal ML Ranking System Without Data Leakage
How to avoid data leakage in a temporal ML ranking system: future-only validation, OOF predictions, stacking, and calibration.
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Building an End-to-End ML Product as a Solo Developer: From Data to Mobile App
A firsthand account of building a complete ML product: data engineering, ranking, MLOps, cloud backend, CI/CD, and a Flutter app.
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