Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure Exam Practice Test

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 an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Create an environment.

Does the solution meet the goal?

You have an Azure Machine Learning workspace.

You plan to run a job to tram a model as an MLflow model output.

You need to specify the output mode of the MLflow model.

Which three modes can you specify? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace.

You plan to use the workspace to set up automated machine learning training for an image classification model.

You need to choose the primary metric to optimize the model training.

Which primary metric should you choose?

You have an Azure Machine Learning workspace named WS1.

You plan to use the Responsible Al dashboard to assess MLflow models that you will register in WS1.

You need to identify the library you should use to register the MLflow models.

Which library should you use?

You have an Azure Machine Learning workspace.

You plan to tune a model hyperparameter when you train the model.

You need to define a search space that returns a normally distributed value.

Which parameter should you use?

You create an Azure Machine learning workspace.

You are use the Azure Machine -learning Python SDK v2 to define the search space for concrete hyperparafneters. The hyper parameters must consist of a list of predetermined, comma-separated.

You need to import the class from the azure ai ml. sweep package used to create the list of values.

Which class should you import?

You use the Azure Machine learning SDK v2 tor Python and notebooks to tram a model. You use Python code to create a compute target, an environment, and a taring script. You need to prepare information to submit a training job.

Which class should you use?