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NEW QUESTION: 1
You are troubleshooting an OSPF adjacency that is stuck in the ExStart state.
What would be the correct step to resolve the problem?
A. Determine whether the neighbor is a DR-Other.
B. Determine whether the hello and dead intervals are the same on both sides.
C. Look for a mismatched IP subnet or mask.
D. Review the MTU settings to ensure that they match.
Answer: D

NEW QUESTION: 2
An analyst is running the Marketing Channel Overview report and notices that there is no revenue created to their social media campaigns. At this point there are many campaigns on Facebook that use tracking code query parameter, "cid=social". Exhibits 1 and 2 show how the social traffic is configured by processing rules of the Marketing Channel Report.
What change should the analyst make to the Marketing Channel processing rules?


A. The "Social Campaigns" processing rule should be set to the tracking code contains "Social".
B. The "Social Networks" processing rule should be changed to a condition of "Any".
C. The "Social Campaigns" marketing channel should be before the "Social Networks" channel in processing order.
D. The "Social Networks" channel should be changed to set the channel's value to "Tracking Code".
Answer: D

NEW QUESTION: 3
Which of the following stage should be matched with the Forecast Category "Omit"?
A. Late pipeline stages
B. Early pipeline stages
C. Closed and Won
D. Mid pipeline
E. Closed and Lost
Answer: E

NEW QUESTION: 4
You create a multi-class image classification deep learning model.
The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images, and retrain the model.
You need to use the Azure Machine Learning SDK to configure the schedule for the pipeline.
Which four 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: Publish the pipeline.
To schedule a pipeline, you'll need a reference to your workspace, the identifier of your published pipeline, and the name of the experiment in which you wish to create the schedule.
Step 2: Retrieve the pipeline ID.
Needed for the schedule.
Step 3: Create a ScheduleRecurrence..
To run a pipeline on a recurring basis, you'll create a schedule. A Schedule associates a pipeline, an experiment, and a trigger.
First create a schedule. Example: Create a Schedule that begins a run every 15 minutes:
recurrence = ScheduleRecurrence(frequency="Minute", interval=15)
Step 4: Define an Azure Machine Learning pipeline schedule..
Example, continued:
recurring_schedule = Schedule.create(ws, name="MyRecurringSchedule",
description="Based on time",
pipeline_id=pipeline_id,
experiment_name=experiment_name,
recurrence=recurrence)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-schedule-pipelines