Microsoft DP-100 Practice Test - Questions Answers, Page 38

HOTSPOT

You download a .csv file from a notebook in an Azure Machine Learning workspace to a data/sample.csv folder on a compute instance. The file contains 10,000 records. You must generate the summary statistics for the data in the file. The statistics must include the following for each numerical column:

* number of non-empty values

* average value

* standard deviation

* minimum and maximum values

* 25th. 50th. and 75th percentiles

You need to complete the Python code that will generate the summary statistics.

Which code segments should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

HOTSPOT

You perform hyper parameter tuning with Azure Machine Learning.

You create the following Python code:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

HOTSPOT

You create an Azure Machine Learning model to include model files and a scorning script. You must deploy the model. The deployment solution must meet the following requirements:

* Provide near real-time inferencing.

* Enable endpoint and deployment level cost estimates.

* Support logging to Azure Log Analytics.

You need to configure the deployment solution.

What should you configure? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You run Azure Machine Learning training experiments. The training scripts directory contains 100 files that includes a file named. amlignore. The directory also contains subdirectories named. /outputs and./logs.

There are 20 files in the training scripts directory that must be excluded from the snapshot to the compute targets. You create a file named. gift ignore in the root of the directory. You add the names of the 20 files to the. gift ignore file. These 20 files continue to be copied to the compute targets.

You need to exclude the 20 files. What should you do?

HOTSPOT

You manage an Azure Machine Learning workspace named workspace1.

You must register an Azure Blob storage datastore in workspace1 by using an access key. You develop Python SDK v2 code to import all modules required to register the datastore.

You need to complete the Python SDK v2 code to define the datastore.

How should you complete the code? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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 train and register an Azure Machine Learning model.

You plan to deploy the model to an online end point.

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution:

Create a Kubernetes online endpoint and set the value of its auth-mode parameter to amyl Token. Deploy the model to the online endpoint.

Does the solution meet the goal?

You create an Azure Machine Learning workspace. You use Azure Machine Learning designer to create a pipeline within the workspace. You need to submit a pipeline run from the designer.

What should you do first?

DRAG DROP

You have an Azure Machine Learning workspace. You are running an experiment on your local computer.

You need to ensure that you can use MLflow Tracking with Azure Machine Learning Python SDK v2 to store metrics and artifacts from your local experiment runs in the workspace.

In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

DRAG DROP

You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.

The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must preview the data profile in Azure Machine Learning studio once the dataset is created.

You need to train the model.

Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.