Azure Machine Learning CLI 2.0 (v2)

At Microsoft Build 2021 we launched the public preview of 2.0 CLI and REST APIs for Azure Machine Learning, enabling users to accelerate the iterative model training and deployment process while tracking the model lifecycle, enabling a complete ML Ops experience.

Try it now using this step by step guide

caiomsouza/aml-cli-v2-in-a-day: Azure Machine Learning CLI V2 Demo (github.com)

What’s new?

The ml extension to the Azure CLI is the improved interface for Azure Machine Learning users. It enables you to train and deploy models from the command line, with features that accelerate scaling the data science process up and out, all while tracking the model lifecycle.

Using the CLI enables you to run distributed training jobs on GPU compute, automatically sweep hyperparameters to improve your results, and then monitor jobs in the AML studio user interface to see all details including important metrics, metadata and artefacts like the trained model, checkpoints and logs.

Additionally, the CLI is optimized to support YAML-based job, endpoint, and asset specifications to enable users to create, manage, and deploy models with proper CI/CD (or GitOps) best practices for an end-to-end MLOps solution.

To get started with the 2.0 machine learning CLI extension for Azure, please check the link here .

Job