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Microsoft AI-900 Exam - Topic 3 Question 89 Discussion

Actual exam question for Microsoft's AI-900 exam
Question #: 89
Topic #: 3
[All AI-900 Questions]

You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.

This is an example of which type of natural language processing workload?

Show Suggested Answer Hide Answer
Suggested Answer: B

Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.


https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

by Rebbecca at Jun 16, 2025, 04:16 AM

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Claudio
2 months ago
Nope, it’s clearly B. No doubt about it!
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Nickolas
3 months ago
Wait, could it be key phrase extraction too?
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Talia
3 months ago
I’m surprised this is a common use case for NLP!
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Fabiola
3 months ago
I agree, it’s all about understanding emotions in text.
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Janey
3 months ago
This is definitely sentiment analysis.
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Gwenn
4 months ago
I thought language detection was about identifying the language of the text, so it can't be that one. Sentiment analysis seems more fitting.
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Deonna
4 months ago
This question feels familiar; I practiced a similar one where we had to identify sentiment analysis in customer feedback.
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Rex
4 months ago
I'm not entirely sure, but I remember something about key phrase extraction being related to identifying important terms, not sentiments.
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Cherry
4 months ago
I think this is about sentiment analysis since it involves determining if reviews are positive or negative.
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Loreen
4 months ago
I'm a bit unsure about this one. The question mentions analyzing customer reviews, but I'm not sure if that automatically means it's a sentiment analysis task. I'll have to double-check my understanding of the different NLP workloads.
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Magda
5 months ago
Okay, I've got this. Sentiment analysis is the process of determining whether a piece of text expresses positive, negative, or neutral sentiment. That's exactly what the question is describing, so I'll go with option B.
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Arthur
5 months ago
Hmm, this is a tricky one. I need to make sure I understand the difference between the various natural language processing tasks. Let me think this through carefully.
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Val
5 months ago
This looks like a straightforward sentiment analysis question. I'll focus on understanding the key details about the customer review analysis and select the appropriate option.
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Norah
8 months ago
Haha, this is like the most basic NLP question ever. If you can't nail sentiment analysis, you might as well just give up on the whole field!
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Anastacia
7 months ago
B) sentiment analysis
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Luke
7 months ago
A) language detection
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Kindra
8 months ago
Hmm, I'm not so sure. Couldn't this also involve key phrase extraction to identify the main topics of the reviews? Maybe a combination of B and C would work best.
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Annabelle
8 months ago
Easy peasy, it's B) sentiment analysis. I could do this in my sleep, it's such a common NLP task these days.
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Rozella
8 months ago
I agree, sentiment analysis is the correct answer here. Determining the overall sentiment of a review is key for this type of application.
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Nu
6 months ago
B) sentiment analysis
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Martha
7 months ago
A) language detection
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Chandra
8 months ago
Definitely sentiment analysis. Analyzing the positivity or negativity of reviews is a classic use case for sentiment analysis in natural language processing.
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Skye
7 months ago
B) sentiment analysis
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Vashti
8 months ago
That's correct! Sentiment analysis is used to determine the sentiment or emotion behind text.
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Louann
8 months ago
A) sentiment analysis
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Alecia
8 months ago
I'm not sure, but I think it could also be C) key phrase extraction.
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Jonell
9 months ago
I agree with Letha, sentiment analysis makes sense for analyzing customer reviews.
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Letha
9 months ago
I think the answer is B) sentiment analysis.
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