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NEW QUESTION: 1
Azure Machine Learning Studioを使用してデータセットを分析しています。
各機能列のp値と一意の値カウントを含む統計サマリーを生成する必要があります。
ユーザーはどちらのモジュールを使用できますか？それぞれの正解は完全な解決策を提示します。
注：それぞれの正しい選択には1ポイントの価値があります。
A. データの要約
B. Pythonスクリプトの実行
C. 線形相関の計算
D. カウントテーブルのエクスポート
E. インジケーター値に変換
Answer: C,D
Explanation:
Explanation
The Export Count Table module is provided for backward compatibility with experiments that use the Build Count Table (deprecated) and Count Featurizer (deprecated) modules.
E: Summarize Data statistics are useful when you want to understand the characteristics of the complete dataset. For example, you might need to know:
How many missing values are there in each column?
How many unique values are there in a feature column?
What is the mean and standard deviation for each column?
The module calculates the important scores for each column, and returns a row of summary statistics for each variable (data column) provided as input.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/export-count-table
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/summarize-data
NEW QUESTION: 2
When configuring FCoE VLANs and Virtual Fiber Channel (vFC) Interfaces, what guidelines must be followed?
A. Each vFC interface must be bound to an FCoE-enabled Ethernet or EtherChannel interface or to the MAC address of a remotely connected adapter
B. Each vFC interface must be bound to an FCoE-enabled vFC or EtherChannel interface or to the MAC address of a remotely connected adapter
C. Each vFC interface must be bound to an FC enabled Ethernet or EtherChannel interface or to the MAC address of a remotely connected adapter
D. Each FC interface must be bound to an FCoE-enabled Ethernet or EtherChannel interface or to the MAC address of a remotely connected adapter
Answer: A
NEW QUESTION: 3
An International company has deployed a multi-tier web application that relies on DynamoDB in a single region. For regulatory reasons they need disaster recovery capability in a separate region with a Recovery Time Objective of 2 hours and a Recovery Point Objective of 24 hours. They should synchronize their data on a regular basis and be able to provision me web application rapidly using CloudFormation.
The objective is to minimize changes to the existing web application, control the throughput of DynamoDB used for the synchronization of data and synchronize only the modified elements.
Which design would you choose to meet these requirements?
A. Use EMR and write a custom script to retrieve data from DynamoDB in the current region using a SCAN operation and push it to DynamoDB in the second region.
B. Use AWS data Pipeline to schedule an export of the DynamoDB table to S3 in the current region once a day then schedule another task immediately after it that will import data from S3 to DynamoDB in the other region.
C. Use AWS data Pipeline to schedule a DynamoDB cross region copy once a day, create a "Lastupdated" attribute in your DynamoDB table that would represent the timestamp of the last update and use it as a filter.
D. Send also each Ante into an SQS queue in me second region; use an auto-scaling group behind the SQS queue to replay the write in the second region.
Answer: C
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