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NEW QUESTION: 1
show frame-relay mapの出力に表示される2つの統計情報はどれですか。 （2つ選んでください。）
A. ローカルルータのIPアドレス
B. ルーターが受信したBECNパケットの数
C. ルータに設定されているPVCのステータス
D. ローカルDLCIの値
E. ルーターによって受信されたFECNパケットの数
Answer: C,D
Explanation:
Frame Relay Commands (map-class frame-relay through threshold ecn)
http://www.cisco.com/en/US/docs/ios/12_2/wan/command/wrffr4.html#wp102934 Examples The following is sample output from the show frame-relay map command:
Router#show frame-relay map Serial 1 (administratively down): ip 10.108.177.177 dlci 177 (0xB1,0x2C10), static, broadcast, CISCO TCP/IP Header Compression (inherited), passive (inherited)

NEW QUESTION: 2
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure ML experiment that contains an intermediate dataset.
You need to explore data from the intermediate dataset by using Jupyter.
Solution: You add a Convert to CSV module to the Azure ML experiment and then open the module output in a new notebook.
Does this meet the goal?
A. Yes
B. No
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Access intermediate datasets from Machine Learning experiments
The following steps show an example that creates an experiment, runs it and accesses the intermediate dataset.
1. Create a new experiment.
2. Insert an Adult Census Income Binary Classification dataset module.
3. Insert a Split module, and connect its input to the dataset module output.
4. Insert a Convert to CSV module and connect its input to one of the Split module outputs.
5. Save the experiment, run it, and wait for it to finish running.
6. Click the output node on the Convert to CSV module.
7. When the context menu appears, select Generate Data Access Code
8. Select the code snippet and copy it to your clipboard from the window that appears..
9. Paste the code in your notebook.
Note: After an experiment is run in the Machine Learning Studio, it is possible to access the intermediate datasets from the output nodes of modules. Intermediate datasets are data that has been created and used for intermediate steps when a model tool has been run.
Intermediate datasets can be accessed as long as the data format is compatible with the Python client library.
The following formats are supported (constants for these are in the azureml.DataTypeIds class):
PlainText

GenericCSV

GenericTSV

GenericCSVNoHeader

GenericTSVNoHeader

References: https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/python- data-access

NEW QUESTION: 3
Welcher der folgenden Schritte verhindert, dass ein Benutzer eine interaktive Anmeldesitzung erhält?
A. Legen Sie die UID für den Benutzer auf 0 fest.
B. Fügen Sie den Benutzer zu / etc / noaccess hinzu.
C. Entfernen Sie den Benutzer aus dem Gruppenpersonal.
D. Erstellen Sie eine .nologin-Datei im Basisverzeichnis des Benutzers.
E. Führen Sie den Befehl chsh -s / bin / false mit dem Benutzernamen aus.
Answer: E
Explanation:
Erläuterung
Abschnitt: Administrative Aufgaben

NEW QUESTION: 4
どのタスクにPRSMを使用できますか？
A. Cisco ASA CXファイアウォールを設定する
B. Cisco ESAを設定する
C. Cisco intelliShieldを監視する
D. CWSのトラフィックを監視する
Answer: A

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