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NEW QUESTION: 1
Was können Sie für einen Benutzerstatus im Statusprofil definieren?
A. Die Auftragstypen, für die ein Benutzerstatus gültig ist
B. Die Versionen, für die Sie Plandaten eingeben können
C. Die Geschäftsbenutzer-IDs, die zum Ändern des Benutzerstatus berechtigt sind
D. Der zugewiesene Benutzerstatus nach Ausführung eines Geschäftsvorfalls
Answer: D
NEW QUESTION: 2
Which cloud computing characteristic enables consumers to request resources using a service catalog through a web-based user interface?
A. Metered services
B. On-demand self-service
C. Catalog management
D. Broad network access
Answer: B
NEW QUESTION: 3
あなたはホテル予約のウェブサイト会社で働いているデータサイエンティストです。 Azure Machine Learningサービスを使用して、不正なトランザクションを識別するモデルをトレーニングします。
Azure Machine Learning SDKのModel.deployメソッドを使用して、モデルをAzure Machine LearningリアルタイムWebサービスとしてデプロイする必要があります。デプロイされたWebサービスは、トランザクションデータ入力に基づいて不正のリアルタイム予測を返す必要があります。
モデルのデプロイに使用されるInferenceConfigクラスのentry_scriptパラメーターとして指定されるスクリプトを作成する必要があります。
入力スクリプトは何をすべきですか？
A. Webサービスコンピューティング用のConda環境を作成し、必要なPythonパッケージをインストールします。
B. 適切なタグとプロパティを使用してモデルを登録します。
C. 推論の計算に必要なコアの数とメモリの量を指定します。
D. Webサービスがデプロイされている推論クラスターでノードを起動します。
E. モデルを読み込み、それを使用して入力データからラベルを予測します。
Answer: E
Explanation:
The entry script receives data submitted to a deployed web service and passes it to the model. It then takes the response returned by the model and returns that to the client. The script is specific to your model. It must understand the data that the model expects and returns.
The two things you need to accomplish in your entry script are:
Loading your model (using a function called init())
Running your model on input data (using a function called run())
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-and-where