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NEW QUESTION: 1
You need to recommend the licenses that will provide access to the company's SharePoint services.
Which license should you recommend?
A. SharePoint Server for Internet Sites Standard
B. Windows Server External Connector (EC)
C. SharePoint Server CAL
D. Windows Server User CAL
Answer: D
NEW QUESTION: 2
Which component of IBM Spectrum Scale enables data to be imported from several servers at the same time?
A. Multi-Cluster feature
B. Cloud Object Storage support
C. HDFS Transparency connector
D. IBM Spectrum Protect integration
Answer: D
NEW QUESTION: 3
Azure Machine Learning SDKを使用して、分類モデルをトレーニングし、その精度メトリックを計算するトレーニング実験を実行します。
新しいデータが利用可能になると、モデルは毎月再トレーニングされます。
バッチ推論パイプラインで使用するモデルを登録する必要があります。
モデルを登録し、その後の再トレーニング実験で作成されたモデルが、現在登録されているモデルよりも精度が高い場合にのみ登録されるようにする必要があります。
この目標を達成するための2つの可能な方法は何ですか？それぞれの正解は完全な解決策を提示します。
注：正しい選択はそれぞれ1ポイントの価値があります。
A. モデルを登録するときに、精度メトリックを値として精度という名前のプロパティを指定し、現在登録されているモデルの精度プロパティ値よりも精度が高い場合にのみ、後続のモデルを登録します。
B. 精度に関係なく、毎回同じ名前でモデルを登録し、バッチ推論パイプラインでは常に最新バージョンのモデルを使用します。
C. モデルを登録するたびに異なる名前を指定してください。
D. モデルを登録するときに、精度メトリックを値として精度という名前のタグを指定し、現在登録されているモデルの精度タグ値よりも精度が高い場合にのみ、後続のモデルを登録します。
E. モデル登録時にモデルフレームワークのバージョンを指定し、この値が大きい場合にのみ後続のモデルを登録します。
Answer: D,E
Explanation:
Explanation
E: Using tags, you can track useful information such as the name and version of the machine learning library used to train the model. Note that tags must be alphanumeric.
Reference:
https://notebooks.azure.com/xavierheriat/projects/azureml-getting-started/html/how-to-use-azureml/deployment/
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