Updated Apr-2023 Exam Materials for You to Prepare & Pass AI-900 Exam [Q73-Q94]

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Updated Apr-2023 Exam Materials for You to Prepare & Pass AI-900 Exam.

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NEW QUESTION 73
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.0

 

NEW QUESTION 74
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
  • B. providing closed captions for recorded or live videos
  • C. creating an automated public address system for a train station
  • D. creating a transcript of a telephone call or meeting

Answer: B,D

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

 

NEW QUESTION 75
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
Explanation
Features

 

NEW QUESTION 76
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Reference:
https://docs.microsoft.com/en-gb/azure/cognitive-services/qnamaker/concepts/data-sources-and-content
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service

 

NEW QUESTION 77
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.

Answer:

Explanation:

Explanation
Graphical user interface, text, application Description automatically generated

Box 1: Image classification
Image classification is a supervised learning problem: define a set of target classes (objects to identify in images), and train a model to recognize them using labeled example photos.
Box 2: Object detection
Object detection is a computer vision problem. While closely related to image classification, object detection performs image classification at a more granular scale. Object detection both locates and categorizes entities within images.
Box 3: Semantic Segmentation
Semantic segmentation achieves fine-grained inference by making dense predictions inferring labels for every pixel, so that each pixel is labeled with the class of its enclosing object ore region.
Reference:
https://developers.google.com/machine-learning/practica/image-classification
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-model-builder
https://nanonets.com/blog/how-to-do-semantic-segmentation-using-deep-learning/

 

NEW QUESTION 78
What are two tasks that can be performed by using the Computer Vision service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. Train a custom image classification model.
  • B. Detect faces in an image.
  • C. Translate the text in an image between languages.
  • D. Recognize handwritten text.

Answer: B,D

Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation:
B: Azure's Computer Vision service provides developers with access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
C: Computer Vision includes Optical Character Recognition (OCR) capabilities. You can use the new Read API to extract printed and handwritten text from images and documents.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/home

 

NEW QUESTION 79
You need to build an image tagging solution for social media that tags images of your friends automatically.
Which Azure Cognitive Services service should you use?

  • A. Form Recognizer
  • B. Computer Vision
  • C. Face
  • D. Text Analytics

Answer: C

 

NEW QUESTION 80
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/get-started-build-detector

 

NEW QUESTION 81
Match the types of computer vision to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: Facial recognition
Face detection that perceives faces and attributes in an image; person identification that matches an individual in your private repository of up to 1 million people; perceived emotion recognition that detects a range of facial expressions like happiness, contempt, neutrality, and fear; and recognition and grouping of similar faces in images.
Box 2: OCR
Box 3: Objection detection
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like "indoor", which can't be localized with bounding boxes.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

 

NEW QUESTION 82
You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. the authentication key
  • B. the training endpoint
  • C. the REST endpoint
  • D. the model name

Answer: C,D

Explanation:
Explanation
A: The trained model is stored as a Dataset module in the module palette. You can find it under My Datasets.
Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.
D: You can consume a published pipeline in the Published pipelines page. Select a published pipeline and find the REST endpoint of it.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-run-batch-predictions-designer
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

 

NEW QUESTION 83
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://azure.microsoft.com/es-es/blog/machine-assisted-text-classification-on-content-moderator-public-preview/
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

 

NEW QUESTION 84
You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments.
This is an example of which Microsoft guiding principle for responsible AI?

  • A. reliability and safety
  • B. fairness
  • C. accountability
  • D. inclusiveness

Answer: D

Explanation:
Explanation
Inclusiveness: At Microsoft, we firmly believe everyone should benefit from intelligent technology, meaning it must incorporate and address a broad range of human needs and experiences. For the 1 billion people with disabilities around the world, AI technologies can be a game-changer.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

 

NEW QUESTION 85
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
Explanation

Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud.
Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/

 

NEW QUESTION 86
You are building an AI system.
Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?

  • A. Ensure that a training dataset is representative of the population.
  • B. Ensure that all visuals have an associated text that can be read by a screen reader.
  • C. Enable autoscaling to ensure that a service scales based on demand.
  • D. Provide documentation to help developers debug code.

Answer: D

Explanation:
Section: Describe Artificial Intelligence workloads and considerations
Explanation/Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

 

NEW QUESTION 87
Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:
Explanation

Box 3: Natural language processing
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

 

NEW QUESTION 88
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Reference:
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features Speech recognition means Speech to Text. In the above example as a person speaks the words are converted into text of the same language. Hence Speech to Text also called Speech recognition is the right answer.
Speech recognition - the ability to detect and interpret spoken input.
Speech synthesis - the ability to generate spoken output.
https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction

 

NEW QUESTION 89
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.

Answer:

Explanation:
Explanation
Graphical user interface, text, application, chat or text message Description automatically generated

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines

 

NEW QUESTION 90
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 website that uses a knowledge base to interactively respond to users' questions
  • B. assembly line machinery that autonomously inserts headlamps into cars
  • C. monitoring the temperature of machinery to turn on a fan when the temperature reaches a specific threshold
  • D. a smart device in the home that responds to questions such as "What will the weather be like today?"

Answer: A,D

Explanation:
Section: Describe features of conversational AI workloads on Azure

 

NEW QUESTION 91
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation:
With Microsoft's Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack, and more.
Reference:
https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect- and-manage-intelligent-bots

 

NEW QUESTION 92
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/get-started-build-detector

 

NEW QUESTION 93
You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?

  • A. XML
  • B. ZIP
  • C. PDF
  • D. PPTX

Answer: C

Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/data-sources-and-content

 

NEW QUESTION 94
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