Online Access Free DP-100 Practice Test

You have an Azure Machine Learning (ML) model deployed to an online endpoint.
You need to review container logs from the endpoint by using Azure Ml Python SDK v2. The logs must include the console log from the inference server with print/log statements from the models scoring script.
What should you do first?

• A.Connect by using Docker tools to the inference server.
• B.Create an instance of the OnlineDeploymentOperations class.
• C.Connect by using SSH to the inference server.
• D.Create an instance of the the MLCIient class.

You manage an Azure Machine Learning workspace
You build an Azure Machine Learning pipeline for image classification by using custom components. You need to define the interface, metadata, and code to execute components from a Python function. Which function should you use?

• A.command_component()
• B.Ioad_component()
• C.from config()
• D.create_or_update()

You use Azure Machine Learning Designer lo load the following datasets into an experiment:
Dataset1:

Dataset2:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.
Solution: Use the Add Rows component.
Does the solution meet the goal?

• A.No
• B.Yes

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.
You plan to add a new Jupyter kernel that will be accessible from the same terminal session.
You need to perform the task that must be completed before you can add the new kernel.
Solution: Create an environment.
Does the solution meet the goal?

• A.No
• B.Yes

You create an Azure Machine Learning workspace. The workspace contains a dataset named sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline that will prepare data in the dataset and then train and register a model based on the prepared data. The first stage of the pipeline contains the following code:

You need to identify the location containing the output of the first stage of the script that you can use as input for the second stage. Which storage location should you use?

• A.workspacefi lest ore datastore
• B.compute instance
• C.workspaceblobstore datastore