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NEW QUESTION: 1
マルチクラスの画像分類の深層学習モデルを作成します。
モデルは、パブリックWebポータルからフェッチされた新しい画像データで毎月再トレーニングする必要があります。 Azure Machine Learningパイプラインを作成して、新しいデータをフェッチし、画像のサイズを標準化し、モデルを再トレーニングします。
パイプラインのスケジュールを構成するには、Azure Machine Learning SDKを使用する必要があります。
どの4つのアクションを順番に実行する必要がありますか。回答するには、適切なアクションをアクションのリストから回答領域に移動し、正しい順序に並べます。
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
NEW QUESTION: 2
Cisco SD-WANソリューションでは、データプレーントンネルの状態はどのように監視されますか？
A. OMPあり
B. BFDの使用
C. ARPプローブ
D. IP SLAあり
Answer: B
NEW QUESTION: 3
Drag and drop the steps in the NAT process for IPv4-initiated packers from the left into the correct sequence on the right.
Answer:
Explanation:
