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Train models in Azure Machine Learning with the CLI (v2)

Microsoft via Microsoft Learn

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Overview

Module 1: Create Azure Machine Learning resources with the CLI (v2)

In this module, you'll learn how to:

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)

In this module, you'll learn how to:

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)

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.

Module 4: Deploy an Azure Machine Learning model to a managed endpoint with CLI (v2)

In this module, you'll learn how to:

Understand managed online endpoints.
Understand how to use managed endpoint with blue/green deployments.
Deploy a MLflow model to a managed online endpoint.

Syllabus

Module 1: Create Azure Machine Learning resources with the CLI (v2)

Introduction
Use the Azure CLI (v2) with Azure Machine Learning
Create an Azure Machine Learning workspace with CLI (v2)
Manage workspace assets with CLI (v2)
Exercise: Create an Azure Machine Learning workspace
Knowledge check
Summary

Module 2: Run jobs in Azure Machine Learning with CLI (v2)

Introduction
Run a Python script as a training job with CLI (v2)
Exercise: Create a basic training job
Run a hyperparameter tuning job with CLI (v2)
Exercise: Run a sweep job
Knowledge check
Summary

Module 3: Use MLflow with Azure Machine Learning jobs submitted with CLI (v2)

Introduction
Track and view model metrics with MLflow
Manage models with MLflow
Exercise: Train and track model with MLflow
Knowledge check
Summary

Module 4: Deploy an Azure Machine Learning model to a managed endpoint with CLI (v2)

Introduction
Explore managed online endpoints
Deploy your model to a managed endpoint
Exercise: Deploy your model with CLI (v2)
Knowledge check
Summary

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