Use MLflow with Azure Machine Learning jobs submitted with CLI (v2)
Use MLflow to track model metrics and artifacts when training and registering models with the Azure Machine Learning CLI (v2).
Learning objectives
In this module, you'll learn how to:
- Automatically track model metrics with MLflow when using common machine learning libraries.
- Track custom metrics with MLflow.
- Use MLflow model assets to register a model in the Azure Machine Learning workspace.
Prerequisites
- Some familiarity with the Azure Machine Learning service.
- Some experience in training machine learning models using frameworks such as scikit-learn.