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NEW QUESTION: 1
A. Option D
B. Option A
C. Option C
D. Option B
E. Option E
Answer: C,D,E
NEW QUESTION: 2
Your network contains an Active Directory domain named contoso.com. The domain contains a DNS server named Server1.
Server1 is configured to use a forwarder named Server2 that has an IP address of 10.0.0.10. Server2 can resolve names hosted on the Internet successfully. Server2 hosts a primary DNS zone named adatum.com.
On Server1, you have the following zone configuration.
The "." zone contains the following records.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Answer:
Explanation:
NEW QUESTION: 3
You are trying to register an H.323-based Cisco TelePresence system to Cisco Unified Communications Manager and a Cisco DX70 system to the Cisco VCS Control. Why do neither of the units want to register?
A. You need Cisco TelePresence Management Suite to register Cisco TelePresence systems.
B. The H.323-based system needs to register tothe Cisco VCS Control with an E.164 number, and the Cisco DX70 needs the TFTP address to register on the Cisco Unified Communications Manager.
C. Both systems need to registertothe Cisco Unified Communications Manager, as the Cisco VCS Control is used only for firewall traversal.
D. Both systems need to register to the Cisco VCS Control, but the H.323-based system needs to have the gatekeeper setting set to "Direct."
E. The H.323-based system needs an E164 number to register to Cisco Unified Communications Manager, and the Cisco DX70 needs to have the MAC address configured first on the Cisco VCS Control.
F. You need Cisco TelePresence Server to register Cisco TelePresence systems.
Answer: B
NEW QUESTION: 4
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