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Databricks recommends deploying ML pipelines as code, rather than deploying individual ML models. The recommended approach for migration is to upgrade ML pipelines to use models in Unity Catalog.
In some cases, you might want to migrate individual models to Unity Catalog for initial testing, or for particularly critical models. The notebook demonstrates how to upgrade existing models to Unity Catalog.
Latihan
Modul
Manage machine learning in production with Azure Databricks - Training
Learn how to manage machine learning models in production with Azure Databricks.
Pensijilan
Microsoft Certified: Azure Data Scientist Associate - Certifications
Manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Python, Azure Machine Learning and MLflow.