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NEW QUESTION: 1
You want to use UTA2 ports for native FC LUN access.
How do you accomplish this task?
A. Configure the UTA2 ports as initiator ports with 10 Gb SFP+ transceivers
B. Configure the UTA2 ports as target ports with 10 Gb SFP+ transceivers
C. Configure the UTA2 ports as initiator ports with 16 Gb SFP+ transceivers
D. Configure the UTA2 ports as target ports with 16 Gb SFP+ transceivers.
Answer: D
Explanation:
Explanation/Reference:
Native Fibre Channel drives attach directly to the Fibre Channel SAN, eliminating the need for a router.
NetApp uses the marketing term "UTA2" to refer to a new generation of network adapters that can be configured as either 10-Gb Ethernet and FCoE ports or as 16-Gb FC initiator or target ports.
References: https://library.netapp.com/ecmdocs/ECMP1636035/html/GUID-EC0DDAEE-1178-48EF- B90D-0A7DF498F71B.html

NEW QUESTION: 2
You are creating a machine learning model in Python. The provided dataset contains several numerical columns and one text column. The text column represents a product's category. The product category will always be one of the following:
* Bikes
* Cars
* Vans
* Boats
You are building a regression model using the scikit-learn Python package.
You need to transform the text data to be compatible with the scikit-learn Python package.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: pandas as df
Pandas takes data (like a CSV or TSV file, or a SQL database) and creates a Python object with rows and columns called data frame that looks very similar to table in a statistical software (think Excel or SPSS for example.
Box 2: transpose[ProductCategoryMapping]
Reshape the data from the pandas Series to columns.
Reference:
https://datascienceplus.com/linear-regression-in-python/

NEW QUESTION: 3
重要なビジネスアプリケーションの可用性を混乱させる可能性のある脆弱性の導入を防ぐのに最も効果的なのは、次のうちどれですか？
A. 論理アクセス制御
B. バージョン管理
C. パッチ管理プロセス
D. 変更管理コントロール
Answer: C