CI/CD Pipeline for ML
Automating the model lifecycle
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Design a CI/CD pipeline for an ML project using GitHub Actions. The pipeline must include: unit tests for data transformations, model integration tests, performance validation (the new model must outperform [BASELINE]), model publication in [MLflow/W&B/other], and automated deployment if thresholds are met.
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Conseil pratique : utilisez une matrice (`matrix`) dans GitHub Actions pour exécuter les tests unitaires et de performance sur plusieurs sous-ensembles de données ou hyperparamètres. Cela détecte plus tôt une éventuelle faiblesse du modèle avant le déploiement.
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