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NEW QUESTION: 1
You need to prevent the device-specific tilting exception. What should you do in the video.js file?
A. Evaluate the canTilt variable. If false, bypass the code that tilts the camera.
B. Evaluate the canTilt variable. If true, bypass the code that tilts the camera.
C. Insert a try statement immediately after line VD01 and a catch block immediately before line VD08. Handle the VideoNotFound exception.
D. Insert a try statement immediately after line VD01 and a catch block immediately before line VD08. Handle the MediaNotFound exception.
Answer: A
NEW QUESTION: 2
A solution developer wants to connect to an integration node which is running on an AIX machine from the IBM Integration Explorer running o a Windows system.
The Windows system does not have the Integration Bus runtime component installed.
The solution developer performs these steps:
-Open the IBM Integration Explorer
-Right-click the Integration Nodes folder, and click Connect to a Remote Broker.
- Supply the Integration node queue manager name, host, port and SVRCONN channel name as SYSTEM.BKR.CONFIG.
-Click Finish to connect to the remote broker.
The operation fails and the remote integration node is not added.
What should the developer expect as a possible reason for this failure?
A. The Integration Bus runtime component must be installed to be able to connect to a remote integration node.
B. The IBM Integration Explorercan connect to integration nodes on Windows or Linux basedsystem only.
C. The logged in user in the Windows system could not have enough privileges to connect to the remote broker.
D. ACLNTCONNchannel with the nameSYSTEM.BKR.CONFIGmust be created on the Windows system.
Answer: B
NEW QUESTION: 3
Azure Machine Learning Designerを使用して、回帰モデルのトレーニングパイプラインを作成します。
入力データ値のデータセットに対して非同期で予測を生成するエンドポイントとして、展開するパイプラインを準備する必要があります。
あなたは何をするべきか?
A. トレーニングパイプラインからリアルタイムの推論パイプラインを作成します。
B. トレーニングパイプラインのクローンを作成します。
C. トレーニングパイプラインのデータセットを[データを手動で入力]モジュールに置き換えます。
D. トレーニングパイプラインからバッチ推論パイプラインを作成します。
Answer: A
Explanation:
Explanation
You must first convert the training pipeline into a real-time inference pipeline. This process removes training modules and adds web service inputs and outputs to handle requests.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-deploy
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/enter-data-manually