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NEW QUESTION: 1

A. Firewall
B. Source VLAN
C. DHCP
D. ACL
E. ISE
Answer: A,E

NEW QUESTION: 2
英語のテキストコンテンツをフランス語のテキストコンテンツに翻訳するための機械学習モデルを構築しています。
テキストコンテンツのシーケンスを学習するには、機械学習モデルを構築してトレーニングする必要があります。
どのタイプのニューラルネットワークを使用する必要がありますか？
A. Multilayer Perceptions (MLPs)
B. Recurrent Neural Networks (RNNs)
C. Convolutional Neural Networks (CNNs)
D. Generative Adversarial Networks (GANs)
Answer: B
Explanation:
To translate a corpus of English text to French, we need to build a recurrent neural network (RNN).
Note: RNNs are designed to take sequences of text as inputs or return sequences of text as outputs, or both.
They're called recurrent because the network's hidden layers have a loop in which the output and cell state from each time step become inputs at the next time step. This recurrence serves as a form of memory. It allows contextual information to flow through the network so that relevant outputs from previous time steps can be applied to network operations at the current time step.
References:
https://towardsdatascience.com/language-translation-with-rnns-d84d43b40571

NEW QUESTION: 3
データをディスクライブラリにバックアップするメリットは何ですか？
A. 靴磨き効果をサポートし、バックアップパフォーマンスを向上
B. 構成済みの専用アプライアンスはバックアップにのみ使用されます
C. バックアップとリカバリのパフォーマンスが向上します
D. オフサイトの要件を満たすための組み込みの移植性を提供します
Answer: C

NEW QUESTION: 4

A. Option A
B. Option B
Answer: A

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