AI-900 practice questions 211–220

1. Question 211 · 236 in bank

   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. Hot Area:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

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

   Source: Adapted from community discussion — mnmcbl

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   

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2. Question 212 · 236 in bank

   Select 2

   In which two scenarios can you use the Form Recognizer service? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

   • AExtract the invoice number from an invoice.
   • BTranslate a form from French to English.
   • CFind image of product in a catalog.
   • DIdentify the retailer from a receipt.

   Show answer

   Answer: AD

   References

   • Microsoft Learn

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3. Question 213 · 236 in bank

   HOTSPOT - Select the answer that correctly completes the sentence. Hot Area:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/intro-to-spatial-analysis-public-preview

   Source: Adapted from community discussion — XtraWest

   

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4. Question 214 · 236 in bank

   HOTSPOT - You have a database that contains a list of employees and their photos. You are tagging new photos of the employees. For each of the following statements select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Hot Area:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/face/overview https://docs.microsoft.com/en-us/azure/cognitive-services/face/concepts/face-detection

   Source: Adapted from community discussion — theLazyGuy

   References

   • Microsoft Learn

   

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5. Question 215 · 236 in bank

   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. Hot Area:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Box 1: Yes - Custom Vision functionality can be divided into two features. Image classification applies one or more labels to an image. Object detection is similar, but it also returns the coordinates in the image where the applied label(s) can be found. Box 2: Yes - The Custom Vision service uses a machine learning algorithm to analyze images. You, the developer, submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of submission. Then, the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Box 3: No - Custom Vision service can be used only on graphic files. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/Custom-Vision-Service/overview

   Source: Adapted from community discussion — aarestu

   

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6. Question 216 · 236 in bank

   You are processing photos of runners in a race. You need to read the numbers on the runners' shirts to identity the runners in the photos. Which type of computer vision should you use?

   • Afacial recognition
   • Boptical character recognition (OCR)
   • Cimage classification
   • Dobject detection

   Show answer

   Answer: B

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7. Question 217 · 236 in bank

   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. Select and Place:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   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/

   References

   • Microsoft Learn

   

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8. Question 218 · 236 in bank

   You use drones to identify where weeds grow between rows of crops to send an instruction for the removal of the weeds. This is an example of which type of computer vision?

   • Aobject detection
   • Boptical character recognition (OCR)
   • Cscene segmentation

   Show answer

   Answer: A

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9. Question 219 · 236 in bank

   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?

   • Afairness
   • Binclusiveness
   • Creliability and safety
   • Daccountability

   Show answer

   Answer: B

   Explanation

   B is the answer. https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai#inclusiveness Inclusiveness mandates that AI should consider all human races and experiences, and inclusive design practices can help developers to understand and address potential barriers that could unintentionally exclude people. Where possible, speech-to-text, text-to-speech, and visual recognition technology should be used to empower people with hearing, visual, and other impairments.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn

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10. Question 220 · 236 in bank

    DRAG DROP - Match the facial recognition tasks to the appropriate questions. To answer, drag the appropriate task from the column on the left to its question on the right. Each task may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point. Select and Place:

    

    This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

    Show the answer figure

    Answer: See figure below

    Explanation

    Box 1: verification - Face verification: Check the likelihood that two faces belong to the same person and receive a confidence score. Box 2: similarity - Box 3: Grouping - Box 4: identification - Face detection: Detect one or more human faces along with attributes such as: age, emotion, pose, smile, and facial hair, including 27 landmarks for each face in the image. Reference: https://azure.microsoft.com/en-us/services/cognitive-services/face/#features

    Source: Adapted from community discussion — idioteque

    References

    • Microsoft Learn
    • Microsoft Learn
    • Microsoft Learn

    

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AI-900 practice, question 211. 236 questions available.