DP-100 Practice Test

DP-100 Practice Test practice questions, page 19 of 21, with answer review and explanations.

Question 91

You create an Azure Machine Learning workspace. You are preparing a local Python environment on a laptop computer. You want to use the laptop to connect to the workspace and run experiments. You create the following config.json file. { "workspace_name" : "ml-workspace" } You must use the Azure Machine Learning SDK to interact with data and experiments in the workspace. You need to configure the config.json file to connect to the workspace from the Python environment. Which two additional parameters must you add to the config.json file in order to connect to the workspace? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

  1. login
  2. resource_group
  3. subscription_id
  4. key
  5. region

Question 92

You are performing a classification task in Azure Machine Learning Studio. You must prepare balanced testing and training samples based on a provided data set. You need to split the data with a 0.75:0.25 ratio. Which value should you use for each parameter? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. Hot Area:

Question 93

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.

  1. Use the Azure Machine Learning studio.
  2. Run the update method of the AmlCompute class in the Python SDK.
  3. Use the Azure portal.
  4. Use the Azure Machine Learning designer.
  5. Run the refresh_state() method of the BatchCompute class in the Python SDK.

Question 94

You have a dataset that contains 2,000 rows. You are building a machine learning classification model by using Azure Learning Studio. You add a Partition and Sample module to the experiment. You need to configure the module. You must meet the following requirements: ✑ Divide the data into subsets ✑ Assign the rows into folds using a round-robin method ✑ Allow rows in the dataset to be reused How should you configure the module? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point. Hot Area:

Question 95

You create a new Azure subscription. No resources are provisioned in the subscription. You need to create an Azure Machine Learning workspace. What are three possible ways to achieve this goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

  1. Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, and resource_group parameters.
  2. Navigate to Azure Machine Learning studio and create a workspace.
  3. Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the az group create function with --name and --location parameters, and then the az ml workspace create function, specifying ג€"w and ג€"g parameters for the workspace name and resource group.
  4. Navigate to Azure Machine Learning studio and create a workspace.
  5. Run Python code that uses the Azure ML SDK library and calls the Workspace.get method with name, subscription_id, and resource_group parameters.