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Microsoft AI-102 Exam

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Question 121
You need to measure the public perception of your brand on social media by using natural language processing.
Which Azure service should you use?



Text Analytics Cognitive Service could be used to quickly determine the public perception for a specific topic, event or brand.
Example: A NodeJS app which pulls Tweets from Twitter using the Twitter API based on a specified search term. Then pass these onto Text Analytics for sentiment scoring before storing the data and building a visualisation in PowerBI.
Reference:
https://www.linkedin.com/pulse/measuring-public-perception-azure-cognitive-services-steve-dalai
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

Question 122
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You build a language model by using a Language Understanding service. The language model is used to search for information on a contact list by using an intent named FindContact.
A conversational expert provides you with the following list of phrases to use for training.
- Find contacts in London.
- Who do I know in Seattle?
- Search for contacts in Ukraine.
You need to implement the phrase list in Language Understanding.
Solution: You create a new intent for location.
Does this meet the goal?



An intent represents a task or action the user wants to perform. It is a purpose or goal expressed in a user's utterance.
Define a set of intents that corresponds to actions users want to take in your application.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-intent

Question 123
You are building a natural language model.
You need to enable active learning.
What should you do?



Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-queries-to-enable-active-learning

Question 124
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You build a language model by using a Language Understanding service. The language model is used to search for information on a contact list by using an intent named FindContact.
A conversational expert provides you with the following list of phrases to use for training.
- Find contacts in London.
- Who do I know in Seattle?
Search for contacts in Ukraine.
You need to implement the phrase list in Language Understanding.
Solution: You create a new entity for the domain.
Does this meet the goal?



Instead use a new intent for location.
Note: An intent represents a task or action the user wants to perform. It is a purpose or goal expressed in a user's utterance.
Define a set of intents that corresponds to actions users want to take in your application.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-intent

Question 125
You are training a Language Understanding model for a user support system.
You create the first intent named GetContactDetails and add 200 examples.
You need to decrease the likelihood of a false positive.
What should you do?



Active learning is a technique of machine learning in which the machine learned model is used to identify informative new examples to label. In LUIS, active learning refers to adding utterances from the endpoint traffic whose current predictions are unclear to improve your model.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-glossary


Question 126
DRAG DROP -
You are building a Language Understanding model for purchasing tickets.
You have the following utterance for an intent named PurchaseAndSendTickets.
Purchase [2 audit business] tickets to [Paris] [next Monday] and send tickets to [[email protected]]
You need to select the entity types. The solution must use built-in entity types to minimize training data whenever possible.
Which entity type should you use for each label? To answer, drag the appropriate entity types to the correct labels. Each entity type may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
Select and Place:
AI-102_126Q.jpg related to the Microsoft AI-102 Exam
Image AI-102_126R.jpg related to the Microsoft AI-102 Exam



Box 1: GeographyV2 -
The prebuilt geographyV2 entity detects places. Because this entity is already trained, you do not need to add example utterances containing GeographyV2 to the application intents.
Box 2: Email -
Email prebuilt entity for a LUIS app: Email extraction includes the entire email address from an utterance. Because this entity is already trained, you do not need to add example utterances containing email to the application intents.
Box 3: Machine learned -
The machine-learning entity is the preferred entity for building LUIS applications.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-geographyv2
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-email
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/reference-entity-machine-learned-entity

Question 127
You have the following C# method.
AI-102_127Q.png related to the Microsoft AI-102 Exam
You need to deploy an Azure resource to the East US Azure region. The resource will be used to perform sentiment analysis.
How should you call the method?



To perform sentiment analysis, we specify TextAnalytics, not ContentModerator.
Possible SKU names include: 'F0','F1','S0','S1','S2','S3','S4','S5','S6','S7','S8'
Possible location names include: westus, eastus
Reference:
https://docs.microsoft.com/en-us/powershell/module/az.cognitiveservices/new-azcognitiveservicesaccount

Question 128
You build a Conversational Language Understanding model by using the Language Services portal.
You export the model as a JSON file as shown in the following sample.
AI-102_128Q.png related to the Microsoft AI-102 Exam
To what does the Weather.Historic entity correspond in the utterance?




Question 129
You are examining the Text Analytics output of an application.
The text analyzed is: `Our tour guide took us up the Space Needle during our trip to Seattle last week.`
The response contains the data shown in the following table.
AI-102_129Q.png related to the Microsoft AI-102 Exam
Which Text Analytics API is used to analyze the text?



Named Entity Recognition (NER) is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The NER feature can identify and categorize entities in unstructured text. For example: people, places, organizations, and quantities.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/named-entity-recognition/overview

Question 130
SIMULATION -
You need to configure bot12345678 support the French (FR-FR) language.
Export the bot to C:\Resources\Bot\Bot1.zip.
To complete this task, use the Microsoft Bot Framework Composer.



Step 1: Open Microsoft Bot Framework Composer
Step 2: Select the bot bot12345678
Step 3: Select Configure.
Step 4: Select the Azure Language Understanding tab
Step 5: Select the Set up Language Understanding button. The Set up Language Understanding window will appear, shown below:
AI-102_130E_1.png related to the Microsoft AI-102 Exam
Step 6: Select Use existing resources and then select Next at the bottom of the window.
Step 7: Now select the Azure directory, Azure subscription, and Language Understanding resource name (French).
Step 8: Select Next on the bottom. Your Key and Region will appear on the next on the next window, shown below:
AI-102_130E_2.png related to the Microsoft AI-102 Exam
Step 9. Select Done -
Reference:
https://docs.microsoft.com/en-us/composer/concept-language-understanding
https://docs.microsoft.com/en-us/composer/how-to-add-luis





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