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You have an app that identifies the coordinates of a product in an image of a supermarket shelf. Which service does the app use?
You plan to build a conversational Al solution that can be surfaced in Microsoft Teams. Microsoft Cortana, and Amazon Alex a. Which service should you use?
DRAG DROP Match the types of machine learning to the appropriate scenarios. To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point.
HOTSPOT For each of The following statements, select Yes If the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point
DRAG DROP Match the Azure OpenAI large language model (LLM) process to the appropriate task. To answer, drag the appropriate process from the column on the left to its task on the right. Each process may be used once, more than once, or not at all. NOTE: Each correct match is worth one point.
An app that analyzes social media posts to identify their tone is an example of which type of natural language processing (NLP) workload?
HOTSPOT Select the answer that correctly completes the sentence.
You build a QnA Maker bot by using a frequently asked questions (FAQ) page. You need to add professional greetings and other responses to make the bot more user friendly. What should you do?
Which two resources can you use to analyze code and generate explanations of code function and code comments? Each correct answer presents a complete solution. NOTE: Each correct answer is worth one point.
HOTSPOT For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Question 31

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Which AI service can you use to interpret the meaning of a user input such as "Call me back later?"

A.
Translator Text
A.
Translator Text
Answers
B.
Text Analytics
B.
Text Analytics
Answers
C.
Speech
C.
Speech
Answers
D.
Language Understanding (LUIS)
D.
Language Understanding (LUIS)
Answers
Suggested answer: D

Explanation:

Language Understanding (LUIS) is a cloud-based AI service, that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis

Question 32

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You are developing a Chatbot solution in Azure.

Which service should you use to determine a user's intent?

A.
Translator Text
A.
Translator Text
Answers
B.
Azure Cognitive Search
B.
Azure Cognitive Search
Answers
C.
Speech
C.
Speech
Answers
D.
Language Understanding (LUIS)
D.
Language Understanding (LUIS)
Answers
Suggested answer: B

Explanation:


Question 33

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You need to make the press releases of your company available in a range of languages.

Which service should you use?

A.
Translator Text
A.
Translator Text
Answers
B.
Text Analytics
B.
Text Analytics
Answers
C.
Speech
C.
Speech
Answers
D.
Language Understanding (LUIS)
D.
Language Understanding (LUIS)
Answers
Suggested answer: A

Explanation:

Translator is a cloud-based machine translation service you can use to translate text in near real-time through a simple REST API call. The service uses modern neural machine translation technology and offers statistical machine translation technology. Custom Translator is an extension of Translator, which allows you to build neural translation systems.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/translator/

Question 34

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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?

A.
language detection
A.
language detection
Answers
B.
sentiment analysis
B.
sentiment analysis
Answers
C.
key phrase extraction
C.
key phrase extraction
Answers
D.
entity recognition
D.
entity recognition
Answers
Suggested answer: B

Explanation:

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

Reference:

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

Question 35

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You use natural language processing to process text from a Microsoft news story.

You receive the output shown in the following exhibit.

Which type of natural languages processing was performed?

A.
entity recognition
A.
entity recognition
Answers
B.
key phrase extraction
B.
key phrase extraction
Answers
C.
sentiment analysis
C.
sentiment analysis
Answers
D.
translation
D.
translation
Answers
Suggested answer: A

Explanation:

Named Entity Recognition (NER) is the ability to identify different entities in text and categorize them into pre-defined classes or types such as: person, location, event, product, and organization.

In this question, the square brackets indicate the entities such as DateTime, PersonType, Skill.

Reference:

https://docs.microsoft.com/en-in/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-entity-linking?tabs=version-3-preview

Question 36

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You are developing a solution that uses the Text Analytics service.

You need to identify the main talking points in a collection of documents.

Which type of natural language processing should you use?

A.
entity recognition
A.
entity recognition
Answers
B.
key phrase extraction
B.
key phrase extraction
Answers
C.
sentiment analysis
C.
sentiment analysis
Answers
D.
language detection
D.
language detection
Answers
Suggested answer: B

Explanation:

Broad entity extraction: Identify important concepts in text, including key

Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.

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

Question 37

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In which two scenarios can you use speech recognition? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

A.
an in-car system that reads text messages aloud
A.
an in-car system that reads text messages aloud
Answers
B.
providing closed captions for recorded or live videos
B.
providing closed captions for recorded or live videos
Answers
C.
creating an automated public address system for a train station
C.
creating an automated public address system for a train station
Answers
D.
creating a transcript of a telephone call or meeting
D.
creating a transcript of a telephone call or meeting
Answers
Suggested answer: B, D

Explanation:

Reference: https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features

Question 38

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You need to build an app that will read recipe instructions aloud to support users who have reduced vision. Which version service should you use?

A.
Text Analytics
A.
Text Analytics
Answers
B.
Translator Text
B.
Translator Text
Answers
C.
Speech
C.
Speech
Answers
D.
Language Understanding (LUIS)
D.
Language Understanding (LUIS)
Answers
Suggested answer: C

Explanation:

Reference:

https://azure.microsoft.com/en-us/services/cognitive-services/text-to-speech/#features

Question 39

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Which two scenarios are examples of a conversational AI workload? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

A.
a telephone answering service that has a pre-recorder message
A.
a telephone answering service that has a pre-recorder message
Answers
B.
a chatbot that provides users with the ability to find answers on a website by themselves
B.
a chatbot that provides users with the ability to find answers on a website by themselves
Answers
C.
telephone voice menus to reduce the load on human resources
C.
telephone voice menus to reduce the load on human resources
Answers
D.
a service that creates frequently asked questions (FAQ) documents by crawling public websites
D.
a service that creates frequently asked questions (FAQ) documents by crawling public websites
Answers
Suggested answer: B, C

Explanation:

B: A bot is an automated software program designed to perform a particular task. Think of it as a robot without a body. C: Automated customer interaction is essential to a business of any size. In fact, 61% of consumers prefer to communicate via speech, and most of them prefer self-service. Because customer satisfaction is a priority for all businesses, selfservice is a critical facet of any customer-facing communications strategy.

Incorrect Answers:

D: Early bots were comparatively simple, handling repetitive and voluminous tasks with relatively straightforward algorithmic logic. An example would be web crawlers used by search engines to automatically explore and catalog web content.

Reference: https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/ai-overview https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/interactive-voice-response-bot

Question 40

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You need to provide content for a business chatbot that will help answer simple user queries.

What are three ways to create question-and answer text by using QnA Maker? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

A.
Generate the questions and answers from an existing webpage.
A.
Generate the questions and answers from an existing webpage.
Answers
B.
Use automated machine learning to train a model based on a file that contains the questions.
B.
Use automated machine learning to train a model based on a file that contains the questions.
Answers
C.
Manually enter the questions and answers.
C.
Manually enter the questions and answers.
Answers
D.
Connect the bot to the Cortana channel and ask questions by using Cortana.
D.
Connect the bot to the Cortana channel and ask questions by using Cortana.
Answers
E.
Import chit-chat content from a predefined data source.
E.
Import chit-chat content from a predefined data source.
Answers
Suggested answer: A, C, E

Explanation:

Automatic extraction

Extract question-answer pairs from semi-structured content, including FAQ pages, support websites, excel files, SharePoint documents, product manuals and policies.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/content-types

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