Machine Learning Pipeline Code Review (Python + MLflow)

For ML engineers: audit pipeline from ingestion to deployment with data leakage detection, model registry, serving API, and drift monitoring.

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Use case

Reviewing Churn Prediction pipeline before production; adding MLflow tracking; diagnosing model degradation

#Machine Learning#MLflow#Python#MLOps#Pipeline

Built-in quality guards

Anti-hallucination

Never invent APIs, functions, or libraries

Format Check

Code runs as-is without modification

Code Completeness

No TODO comments or stubs

Security Check

OWASP Top 10 considered in code

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