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NEW QUESTION: 1
Refer to the following alert configuration: Which statement describes the behavior of this alert?

A. It fires when the event count for the current minute is 25% lower than the mean value for the previous 10 minutes.
B. It fires when the event count for the last 10 minutes is 25% lower than the mean value for the previous day.
C. It fires when the event count for the last 10 minutes is 25% greater than for the 10 minutes prior to that.
D. It fires when the event count for the current minute is 25% greater than the mean value for the previous day.
Answer: A

NEW QUESTION: 2
How can you find out which application the Finder will use to open a specific document?
A. Select the document icon in the Finder, choose Get Info from the File menu, and click the disclosure triangle next to "Open with" in the Info window to reveal the selected application in the pop-up menu.
B. Select the document icon in the Finder, choose Show Inspector from the File menu, click Application Bindings in the Inspector window, and scroll to locate the selected application in the pop-up menu.
C. Select the document icon in the Finder, and choose Show Default Application from the File menu.
D. Control-click the document icon in the Finder, and choose Show Application from the shortcut menu.
Answer: A

NEW QUESTION: 3
An enterprise has a large backlog of IT projects. The current strategy is to execute projects as they are submitted, but executive management does not believe this method is optimal. Which of the following is the MOST important action to address this concern?
A. Implement stage-gating to determine the value of each project.
B. Establish a performance dashboard that determines business value.
C. Create a combined business/IT committee to determine project prioritization.
D. Implement a methodology to prioritize projects based on resource availability.
Answer: C

NEW QUESTION: 4
You have an Azure Machine Learning workspace that contains a CPU-based compute cluster and an Azure Kubernetes Services (AKS) inference cluster. You create a tabular dataset containing data that you plan to use to create a classification model.
You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a response.
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.

Answer:
Explanation:

Explanation:
Step 1: Create and start a Compute Instance
To train and deploy models using Azure Machine Learning designer, you need compute on which to run the training process, test the model, and host the model in a deployed service.
There are four kinds of compute resource you can create:
Compute Instances: Development workstations that data scientists can use to work with data and models.
Compute Clusters: Scalable clusters of virtual machines for on-demand processing of experiment code.
Inference Clusters: Deployment targets for predictive services that use your trained models.
Attached Compute: Links to existing Azure compute resources, such as Virtual Machines or Azure Databricks clusters.
Step 2: Create and run a training pipeline..
After you've used data transformations to prepare the data, you can use it to train a machine learning model. Create and run a training pipeline Step 3: Create and run a real-time inference pipeline After creating and running a pipeline to train the model, you need a second pipeline that performs the same data transformations for new data, and then uses the trained model to inference (in other words, predict) label values based on its features. This pipeline will form the basis for a predictive service that you can publish for applications to use.
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/