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NEW QUESTION: 1
ステートフルNAT64の仕様（３つ選んでください）
A. 1 - 1：N変換2 - IPv4アドレスを節約します。3 - アドレスのオーバーロードを使用します。したがって、エンドツーエンドのアドレスの透明性に欠けます。 IPv6アドレスの割り当て6 - IPv6アドレスの割り当てのモードを自由に選択できます。マニュアル、DHCPv6、SLAAC
B. 1：Nの翻訳
C. アドレスオーバーロードを使用するため、エンドツーエンドのアドレス透過性に欠けます
D. IPv4アドレスを節約する
Answer: B,C,D

NEW QUESTION: 2
医学研究プロジェクトでは、事前定義された脳出血タイプに分類された脳スキャン画像の匿名化された大規模なデータセットを使用します。
機械学習を使用して、画像を人がレビューする前に、画像内のさまざまな脳出血タイプの早期検出をサポートする必要があります。
これは、どのタイプの機械学習の例ですか？
A. 回帰
B. クラスタリング
C. 分類
Answer: C
Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/int

NEW QUESTION: 3
Which three elements are part of the Customer Data Feed? (Choose three.)
A. GCDevice
B. Geo-Code
C. Device
D. Event Time
E. IP Address
F. Unrealized Traits
Answer: C,D,E

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