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A00-405 Exam Dumps : SAS Viya 3.5 Natural Language Processing and Computer Vision

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SAS Viya 3.5 Natural Language Processing and Computer Vision Questions and Answers

Question 1

Refer to the Exhibit Tab:

An analyst is trying to find Aviation Safety Reports (ASR) related to taxiway and runway incursions

• She does not know the LITI language

• She finds that 3 of the 14 derived topics have keywords related to incursion incidents.

• She would like to examine documents that discuss incursions from the current ASR document collection

Which strategy will best support the analyst's goals?

Options:

A.

Use the Concepts node to define an INCURSION concept then include this concept in a category rule in the Categories node to identify documents having the INCURSION concept

B.

Use the Merge topics feature of the Topics node to combine the 3 topics, add the merged topic as a category, and then use the Categories node to categorize documents with respect to the category rules derived using the merged topic Examine the matched documents for the incursion category rule.

C.

Save the output data from the Topics results window and use the Explore and Visualize Data component of SAS Viya

D.

Add each of the 3 individual topics as categories then create a category rule in the Categories node that combines the three topic categories using a Boolean OR operation Examine the matched documents fix the incursion category rule

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Question 2

Consider a 224x224 image provided as input for training a CNN for image classification A 5x5 filter is to be used with a stride of 1 for the first convolutional layer What size padding should be applied in order to maintain the original resolution to provide as input to the next layer?

Enter your numeric answer in the space above.

Options:

Question 3

Which statement is TRUE regarding the impact of node placement"?

Options:

A.

When a Concept node appears after a Text Parsing node, only kept terms derived by the Text Parsing node can be used in concept creation

B.

When a Concept node is placed after a Text Parsing node: the term table is affected by the concepts defined in the Concept node and the concepts impact every node that follows the Concept node

C.

When the Concept node appears before the Text Parsing node in the pipeline, the spell-checking features of the Concept node produce parent and child terms that show up as synonyms in the term table created by the Text Parsing node

D.

When a Concept node is placed before a Text Parsing node the term table is affected by the concepts defined in the Concept node and the concepts impact every node that follows the Text Parsing node