
Explanation:
Instantiate an object of the MLClient class. In the Azure Machine Learning Python SDK, the MLClient class is used to manage Azure Machine Learning resources. You can use it to access your workspaces, experiments, and other resources.
Retrieve the tracking URI of workspace1. The tracking URI is used by MLflow to log metrics and artifacts for a specific experiment. You can get this URI from the workspace object.
Set the MLflow tracking URI. MLflow is a platform for managing the machine learning lifecycle. It provides a set of APIs and services that you can use to log and retrieve metrics and artifacts from your machine learning experiments. After getting the tracking URI from the workspace, you should set it as the tracking URI for MLflow.