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NEW QUESTION: 1
How could IT as a Service help drive business outcomes?
A. Providing an organization with various options for the types of services to deploy.
B. By the fast technology acquisition options for the customers.
C. Providing an organization with the right to use the technology and service without the need for purchasing it.
D. Depending upon what the business is seeking, each type of service has different financial implications for business outcomes.
Answer: D

NEW QUESTION: 2
You can also use the template mode IPSEC remote-address is the address specified above.
A. False
B. True
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。
B. 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。
C. 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。
D. 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。
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:
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


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