Exam Name: | Designing and Implementing a Data Science Solution on Azure | ||
Exam Code: | DP-100 Dumps | ||
Vendor: | Microsoft | Certification: | Microsoft Azure |
Questions: | 441 Q&A's | Shared By: | emrys |
You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2.
The default datastore of workspace1 contains a folder named sample_data. The folder structure contains the following content:
You write Python SDK v2 code to materialize the data from the files in the sample.data folder into a Pandas data frame. You need to complete the Python SDK v2 code to use the MLTaWe folder as the materialization blueprint. How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You manage an Azure Machine Learning workspace named Workspace1 and an Azure Blob Storage accessed by using the URL https://storage1.blob.core.wmdows.net/data1.
You plan to create an Azure Blob datastore in Workspace1. The datastore must target the Blob Storage by using Azure Machine Learning Python SDK v2. Access authorization to the datastore must be limited to a specific amount of time.
You need to select the parameters of the Azure Blob Datastore class that will point to the target datastore and authorize access to it.
Which parameters should you use? To answer, select the appropriate options in the answer area
NOTE: Each correct selection is worth one point.
You manage an Azure Machine Learning workspace by using the Python SDK v2.
You must create a compute cluster in the workspace. The compute cluster must run workloads and properly handle interruptions. You start by calculating the maximum amount of compute resources required by the workloads and size the cluster to match the calculations.
The cluster definition includes the following properties and values:
• name="mlcluster1’’
• size="STANDARD.DS3.v2"
• min_instances=1
• maxjnstances=4
• tier="dedicated"
The cost of the compute resources must be minimized when a workload is active Of idle. Cluster property changes must not affect the maximum amount of compute resources available to the workloads run on the cluster.
You need to modify the cluster properties to minimize the cost of compute resources.
Which properties should you modify? 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 have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.
You must run the script as an Azure ML experiment on a compute cluster named aml-compute.
You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.
Solution: Run the following code:
Does the solution meet the goal?