- Module 1: Create Azure Machine Learning resources with the CLI (v2)
- Install the Azure CLI and the Azure Machine Learning extension.
- Create an Azure Machine Learning workspace.
- Manage assets in the Azure Machine Learning workspace.
- Module 2: Run jobs in Azure Machine Learning with CLI (v2)
- Train a model with a Python script using the CLI (v2).
- Perform hyperparameter tuning with the CLI (v2).
- Module 3: Use MLflow with Azure Machine Learning jobs submitted with CLI (v2)
- 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.
- Module 4: Deploy an Azure Machine Learning model to a managed endpoint with CLI (v2)
- Understand managed online endpoints.
- Understand how to use managed endpoint with blue/green deployments.
- Deploy a MLflow model to a managed online endpoint.
In this module, you'll learn how to:
In this module, you'll learn how to:
In this module, you'll learn how to:
In this module, you'll learn how to:
