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NEW QUESTION: 1
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、指定された目標を満たす可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合がありますが、他の質問セットには正しい解決策がない場合があります。
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IT部門は、次のAzureリソースグループとリソースを作成します。
IT部門は、Azure Machine Learningワークスペースにaks-clusterという名前のAzure Kubernetes Service（AKS）ベースの推論コンピューティングターゲットを作成します。
GPUを搭載したMicrosoft Surface Bookコンピュータを使用しています。 Python 3.6とVisual Studio Codeがインストールされています。
ディープニューラルネットワーク（DNN）モデルをトレーニングし、損失と精度のメトリックをログに記録するスクリプトを実行する必要があります。
解決策：Azure Machine Learningワークスペースで、mlvm仮想マシンをコンピューティングターゲットとして接続します。
Azure ML SDKをSurface Bookにインストールし、Pythonコードを実行してワークスペースに接続します。 mlvmリモートコンピューティングリソースで実験としてトレーニングスクリプトを実行します。
A. はい
B. いいえ
Answer: A
Explanation:
Use the VM as a compute target.
Note: A compute target is a designated compute resource/environment where you run your training script or host your service deployment. This location may be your local machine or a cloud-based compute resource.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target
NEW QUESTION: 2
Match each adapter to its characteristic.
Answer:
Explanation:
NEW QUESTION: 3
HOTSPOT
Answer:
Explanation:
Explanation: