What does the Azure Machine Learning CLI extension facilitate?

The Azure Machine Learning CLI (Command-Line Interface) extension facilitates easier configuration of resources with Azure DevOps and GitHub by providing a set of commands that streamline the management of machine learning resources and workflows. This integration allows data scientists and machine learning engineers to efficiently manage and automate deployments of their machine learning models and pipelines directly from the command line.

Through this CLI, users can easily access and control Azure Machine Learning services, enabling tasks such as creating and managing compute resources, datasets, and experiments more seamlessly. The capability to integrate with Azure DevOps and GitHub enhances the continuous integration and continuous deployment (CI/CD) processes, allowing teams to adopt best practices in collaborative development while ensuring consistency in the deployment of machine learning models.

In contrast, the other options focus on different areas. Data access management typically refers to how data is secured and accessed, which is not the primary function of the Azure Machine Learning CLI. Code optimization relates more to improving the performance and efficiency of software code rather than resource management. Basic data visualization involves creating visual representations of data, which is a different aspect of handling machine learning tasks and not the focus of the CLI extension.