Free Microsoft DP-100 Exam Questions

Question 1

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment. You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets. You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort. What should you do?

A : Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.

B : Always run the experiment with an Estimator by using the default packages.

C : Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.

D : Create a config. yaml file defining the conda packages that are required and save the file in the experiment folder.

E : Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.

Answer: A

Question 2

You create a training pipeline by using the Azure Machine Learning designer. You need to load data into a machine learning pipeline by using the Import Data component. Which two data sources could you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point

A : ure Blob storage container through a registered datastore

B : ure SQL Database

C : L via HTTP

D : ure Data Lake Storage Gen2

E : gistered dataset

Answer: A,C

Question 3

You use Azure Machine Learning Studio to build a machine learning experiment. You need to divide data into two distinct datasets. Which module should you use?

A : Split Data

B : Load Trained Model

C : Assign Data to Clusters

D : Group Data into Bins

Answer: D

Question 4

You create an Azure Machine Learning compute resource to train models. The compute resource is configured

as follows:

Minimum nodes: 2

Maximum nodes: 4

You must decrease the minimum number of nodes and increase the maximum number of nodes to the

following values:

Minimum nodes: 0

Maximum nodes: 8

You need to reconfigure the compute resource.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution

NOTE: Each correct selection is worth one point.

A : the Azure Machine Learning studio.

B : n the update method of the AmlCompute class in the Python SDK.

C : the Azure portal.

D : the Azure Machine Learning designer.

E : n the refresh_state() method of the BatchCompute class in the Python SDK

Answer: A,B,C

Question 5

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment. You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets. You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort. What should you do?