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HOTSPOT You create an Azure Machine Learning dataset containing automobile price data The dataset includes 10,000 rows and 10 columns You use Azure Machine Learning Designer to transform the dataset by using an Execute Python Script component and custom code. The code must combine three columns to create a new column. You need to configure the code function. Which configurations should you use? lo answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
DRAG DROP You create an Azure Machine Learning workspace and an Azure Synapse Analytics workspace with a Spark pool. The workspaces are contained within the same Azure subscription. You must manage the Synapse Spark pool from the Azure Machine Learning workspace. You need to attach the Synapse Spark pool in Azure Machine Learning by usinq the Python SDK v2. 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 use Azure Machine Learning studio to analyze an mltable data asset containing a decimal column named column1. You need to verify that the column1 values are normally distributed. Which statistic should you use?
You register a model that you plan to use in a batch inference pipeline. The batch inference pipeline must use a ParallelRunStep step to process files in a file dataset. The script has the ParallelRunStep step runs must process six input files each time the inferencing function is called. You need to configure the pipeline. Which configuration setting should you specify in the ParallelRunConfig object for the PrallelRunStep step?
HOTSPOT You create an Azure Machine Learning model to include model files and a scorning script. You must deploy the model. The deployment solution must meet the following requirements: * Provide near real-time inferencing. * Enable endpoint and deployment level cost estimates. * Support logging to Azure Log Analytics. You need to configure the deployment solution. What should you configure? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
You train and publish a machine teaming model. You need to run a pipeline that retrains the model based on a trigger from an external system. What should you configure?
You create a multi-class image classification deep learning model. You train the model by using PyTorch version 1.2. You need to ensure that the correct version of PyTorch can be identified for the inferencing environment when the model is deployed. What should you do?
You plan to create a speech recognition deep learning model. The model must support the latest version of Python. You need to recommend a deep learning framework for speech recognition to include in the Data Science Virtual Machine (DSVM). What should you recommend?
DRAG DROP You are analyzing a raw dataset that requires cleaning. You must perform transformations and manipulations by using Azure Machine Learning Studio. You need to identify the correct modules to perform the transformations. Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module 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 manage an Azure Machine learning workspace. You develop a machine teaming model. You are deploying the model to use a low-pointy VM mm a pacing discount. You need to deploy the model. Which compute large! should you use?

Question 117 - DP-100 discussion

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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: Attach the mlvm virtual machine as a compute target in the Azure Machine Learning workspace. Install the Azure ML SDK on the Surface Book and run Python code to connect to the workspace. Run the training script as an experiment on the mlvm remote compute resource.

Does the solution meet the goal?

A.
Yes
Answers
A.
Yes
B.
No
Answers
B.
No
Suggested answer: A

Explanation:

Use the VM as a compute target.

Note: A compute target is a designated compute resource/environment where you run your training script or host your service deployment. This location may be your local machine or a cloud-based compute resource.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target

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asked 02/10/2024
Kabi Bashala
32 questions
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