DP-100試験無料問題集「Microsoft Designing and Implementing a Data Science Solution on Azure 認定」
You manage an Azure Machine Learning workspace. You develop a regression model training pipeline by using Notebooks. You need to determine the appropriate evaluation metric for the experiment.
Which two metrics should you choose? Each correct answer presents a complete solution. Choose two. NOTE: Each correct selection is worth one point.
Which two metrics should you choose? Each correct answer presents a complete solution. Choose two. NOTE: Each correct selection is worth one point.
正解：A,C
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You set up a machine learning workflow as an automated process. You have an Owner role in an Azure subscription that contains the Azure Machine Learning workspace.
You must set up an authentication method that allows an automated process to authenticate to the workspace without requiring user interaction.
You need to set up the authentication for the Azure Machine Learning workspace.
Which three authentication steps should you perform in sequence? To answer, move the appropriate authentication steps from the list of authentication steps to the answer area and arrange them in the correct order.
NOTE More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
You must set up an authentication method that allows an automated process to authenticate to the workspace without requiring user interaction.
You need to set up the authentication for the Azure Machine Learning workspace.
Which three authentication steps should you perform in sequence? To answer, move the appropriate authentication steps from the list of authentication steps to the answer area and arrange them in the correct order.
NOTE More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
正解：
You create a deep learning model for image recognition on Azure Machine Learning service using GPU-based training.
You must deploy the model to a context that allows for real-time GPU-based inferencing.
You need to configure compute resources for model inferencing.
Which compute type should you use?
You must deploy the model to a context that allows for real-time GPU-based inferencing.
You need to configure compute resources for model inferencing.
Which compute type should you use?
正解：C
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解説: (GoShiken メンバーにのみ表示されます)
You create a new Azure Machine Learning workspace with a compute cluster.
You need to create the compute cluster asynchronously by using the Azure Machine Learning Python SDK v2.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
You need to create the compute cluster asynchronously by using the Azure Machine Learning Python SDK v2.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
正解：
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.
An IT department creates the following Azure resource groups and resources:
The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.
You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.
You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on local compute.
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.
An IT department creates the following Azure resource groups and resources:
The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.
You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.
You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on local compute.
正解：A
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解説: (GoShiken メンバーにのみ表示されます)
You use Azure Machine Learning designer to create a training pipeline for a regression model.
You need to prepare the pipeline for deployment as an endpoint that generates predictions asynchronously for a dataset of input data values.
What should you do?
You need to prepare the pipeline for deployment as an endpoint that generates predictions asynchronously for a dataset of input data values.
What should you do?
正解：A
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解説: (GoShiken メンバーにのみ表示されます)
You manage an Azure Machine Learning workspace named workspaces
You plan to create a registry named registry01 with the help of the following registry.yml (line numbers are used for reference only):
You need to use Azure Machine Learning Python SDK v2 with Python 3.10 in a notebook to interact with workspace1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
You plan to create a registry named registry01 with the help of the following registry.yml (line numbers are used for reference only):
You need to use Azure Machine Learning Python SDK v2 with Python 3.10 in a notebook to interact with workspace1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
正解：
You manage an Azure Machine Learning workspace. You build a model for which you must configure a Responsible Al dashboard. Based on what you learn from the dashboard, you must perform the following activities:
* Determine what must be done to get a desirable outcome from the model.
* Identify the features that have the most direct effect on your outcome of interest.
You need to select the components to use for the Responsible Al dashboard configuration. Which two components should you add? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
* Determine what must be done to get a desirable outcome from the model.
* Identify the features that have the most direct effect on your outcome of interest.
You need to select the components to use for the Responsible Al dashboard configuration. Which two components should you add? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
正解：A,D
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