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NEW QUESTION: 1
クラウドコンピューティングのビルディングブロックと見なされるのは次のうちどれですか?
A. ストレージ、ネットワーキング、印刷、仮想化
B. CPU、RAM、ストレージ、ネットワーク
C. データ、CPU、RAM、およびアクセス制御
D. データ、アクセス制御、仮想化、およびサービス
Answer: B

NEW QUESTION: 2
You need to define an evaluation strategy for the crowd sentiment models.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation

Scenario:
Experiments for local crowd sentiment models must combine local penalty detection data.
Crowd sentiment models must identify known sounds such as cheers and known catch phrases. Individual crowd sentiment models will detect similar sounds.
Note: Evaluate the changed in correlation between model error rate and centroid distance In machine learning, a nearest centroid classifier or nearest prototype classifier is a classification model that assigns to observations the label of the class of training samples whose mean (centroid) is closest to the observation.
References:
https://en.wikipedia.org/wiki/Nearest_centroid_classifier
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/sweep-clustering

NEW QUESTION: 3
アーキテクトは、Horizo​​n VDI環境でのパフォーマンスの低下を分析し、ユーザーエクスペリエンスを改善する方法に関する推奨事項を提供するよう求められます。
建築家のドキュメント:
-vSANを使用する4ノードのESXiクラスター
-各ノードには128GBのRAM、4つの500GB 10K HDD、1つの200GB SSDがあります
-各デスクトップは4GBのRAMと2vCPUで構成されています
-各デスクトップには20 GBのワーキングセットがあります
-環境のピークは、使用中の同時デスクトップ150台
アーキテクトはどのようなアクションを推奨できますか?
A. 各ESXiホストに3つの追加の200GB SSDドライブを追加します。
B. 仮想デスクトップに割り当てられているRAMを増やします。
C. 仮想デスクトップに割り当てられたすべてのRAMを予約します。
D. 各ESXiホストに200GB SSDを追加します。
Answer: B


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