SAS Viya 3.5 Natural Language Processing and Computer Vision A00-405 Real Practice Questions

SAS Viya 3.5 Natural Language Processing and Computer Vision A00-405 exam is one of the SAS Institute certification exams, which is one of the required exams for AI & Machine Learning (SAS Certified Professional: AI & Machine Learning) certification. Real A00-405 practice questions from ITExamShop which were written by the top experts should be the best materials online for starting at the preparation of actual SAS Institute A00-405 exam. ITExamShop SAS Institute A00-405 real practice questions with the precise answers will direct you on how you can clear A00-405 test without investing a lot of energy.

A00-405 Free Questions As the Demo OF Real Practice Questions Are Recommended To Read Below

Page 1 of 1

 Loading...

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?

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

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.

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

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

Launch demo modal

 Loading...

2. What are two reasons to use a pooling layer in a Convolution Neural Network (CNN)? (Choose two)

to increase granularity of information

to make the feature map invariant to transformation

to extract features of different spatial scale

to extract a summarized value from an area of the image

Launch demo modal

 Loading...

3. Given the code to add a concatenation layer:





Assume the output dimensions (width*depth):

• source layer A 100*100*5

• source layer B 100*100*5

• source layer C 100*100*3

What is the correct dimension of the output of this concatenation layer?

100'100'13

300'300'5

100'100'18

300'300'13

Launch demo modal

 Loading...

4. Consider the category rule:





Which statement is TRUE about a document that satisfies this rule?

It exhibits the topic named INCURSION

It exhibits one or more of the items used to define the INCURSION concept

It contains the term "incursion" or any of the stemmed versions of "incursion '

It satisfies a previously defined INCURSION category rule but overrides the primary Boolean operator in the original rule with the OR operator

Launch demo modal

 Loading...

5. Given the code:





How many trainable parameters do these lines add to the model

25

520

250

500

Launch demo modal

 Loading...

6. CORRECT TEXT

Assume no padding is used for the input.

What is the output feature map size created by the cross-correlation between a three color channel, 10*10 input and a 4"4 filter that has a stride of two?





Enter your numeric answers in the spaces above

Launch demo modal

 Loading...

7. Refer to the exhibit.





Which statements are TRUE? (Choose two)

More proper nouns terms than the pronouns terms are kept

There are 9 concepts in total

There are 2 custom concepts

Most preposition terms are kept

Launch demo modal

 Loading...