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NEW QUESTION: 1
ネットワークデバイス定義を作成する際に必要なフィールドは次のうちどれですか？
A. SNMP設定
B. バージョン名
C. IPアドレスとサブネットマスク
D. ネットワークデバイスグループ
E. モデル名
Answer: A,C,D
Explanation:
ネットワークデバイス定義を作成するときは、IPアドレスとサブネットマスクが必要です。これらのアドレスは、登録されているデバイスに関連付けられています。 IPアドレスがルーティング可能なIPアドレスである場合、Identity Services Engine（ISE）アプライアンスと通信できることが推奨されます。
ネットワークデバイス定義を作成する場合、ネットワークデバイスグループが必要です。ネットワークデバイスグループを指定する場合、場所とデバイスタイプをデバイスに関連付ける必要があります。
ネットワークデバイス定義を作成する場合、SNMP設定が必要です。必要なSNMP設定は、SNMPバージョン、SNMP ROコミュニティ、およびセキュリティレベルです。 SNMPバージョン1または2cを使用する場合、SNMP ROコミュニティ設定が必要です。 SNMPバージョン3を使用する場合、SNMPユーザー名の設定が必要です。
ネットワークデバイス定義を作成する場合、バージョン名は不要です。このフィールドは、デバイスのソフトウェアバージョン番号を指定するために使用されます。これはオプションのフィールドです。
ネットワークデバイス定義を作成する場合、モデル名は必要ありません。このフィールドは、デバイスのモデル番号を指定するために使用されます。これはオプションのフィールドです。

NEW QUESTION: 2
Which of the following is correct about MongoDB?
A. MongoDB supports collection joins
B. MongoDB supports geospatial indexes
C. MongoDB uses JSON format to represent documents
D. MongoDB supports some of the SQL functions
Answer: B

NEW QUESTION: 3
Which two tools enable you to control a project? (Each correct answer presents part of the solution. Choose two.)
A. project forecasts
B. project statements
C. project budgets
D. project quotations
Answer: A,C

NEW QUESTION: 4
You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?
A. Call the Cloud Natural Language API from your application. Process the generated Entity Analysis as labels.
B. Build and train a text classification model using TensorFlow. Deploy the model using a Kubernetes Engine cluster. Call the model from your application and process the results as labels.
C. Call the Cloud Natural Language API from your application. Process the generated Sentiment Analysis as labels.
D. Build and train a text classification model using TensorFlow. Deploy the model using Cloud Machine Learning Engine. Call the model from your application and process the results as labels.
Answer: A