Pass Using DP-100 Exam Dumps

An organization uses Azure Machine Learning service and wants to expand their use of machine learning.

You have the following compute environments. The organization does not want to create another compute environment.

You need to determine which compute environment to use for the following scenarios.

Which compute types should you use? To answer, drag the appropriate compute environments to the correct scenarios. Each compute environment may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace.

You run the following code in a Python environment in which the configuration file for your workspace has been downloaded.

instructions: For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace named workspace1 with a compute instance named compute1. You connect to compute! by using a terminal window from wofkspace1. You create a file named "requirements.txt" containing Python dependencies to include Jupyler.

You need to add a new Jupyter kernel to compute1.

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

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 are using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model. You configure a HyperDriveConfig for the experiment by running the following code:

variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted. You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric. Solution: Run the following code:

Does the solution meet the goal?