Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 281:

  You need to create a model that labels a collection of your personal digital photographs.

  Which Azure Cognitive Services service should you use?

  A. Form Recognizer
  B. Custom Vision
  C. Language
  D. Computer Vision
  D. Computer Vision

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  Explanation

  Computer Vision, an AI service that analyzes content in images and video.

  Extract rich information from images and video Boost content discoverability, automate text extraction, analyze video in real time, and create products that more people can use by embedding cloud vision capabilities in your apps with Computer Vision, part of Azure Cognitive Services. Use visual data processing to label content with objects and concepts, extract text, generate image descriptions, moderate content, and understand people's movement in physical spaces. No machine learning expertise is required.

  References:

  https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/

• Question 282:

  HOTSPOT

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

  

  

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  References:

  https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

• Question 283:

  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.

  

  

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  Box 1: Yes

  Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality.

  Box 2: No

  Box 3: Yes

  During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through ML algorithms paired with feature selections, where each iteration produces a model with a training score. The higher the score, the better the model is considered to "fit" your data. It will stop once it hits the exit criteria defined in the experiment.

  Box 4: No

  Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.

  The label is the column you want to predict.

  References:

  https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

• Question 284:

  What is an advantage of using a custom model in Form Recognizer?

  A. Only a custom model can be deployed on-premises.
  B. A custom model can be trained to recognize a variety of form types.
  C. A custom model is less expensive than a prebuilt model.
  D. A custom model always provides higher accuracy.
  B. A custom model can be trained to recognize a variety of form types.

• Question 285:

  HOTSPOT

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

  

  

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  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features

• Question 286:

  In which two scenarios can you use a speech synthesis solution? Each correct answer presents a complete solution.

  NOTE: Each correct selection is worth one point.

  A. an automated voice that reads back a credit card number entered into a telephone by using a numeric keypad
  B. generating live captions for a news broadcast
  C. extracting key phrases from the audio recording of a meeting
  D. an AI character in a computer game that speaks audibly to a player
  A. an automated voice that reads back a credit card number entered into a telephone by using a numeric keypad
  D. an AI character in a computer game that speaks audibly to a player

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  Explanation

  Azure Text to Speech is a Speech service feature that converts text to lifelike speech.

  Incorrect Answers:

  C: Extracting key phrases is not speech synthesis.

  References:

  https://azure.microsoft.com/en-in/services/cognitive-services/text-to-speech/

• Question 287:

  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.

  

  

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  Box 1: Yes

  Image classification is a popular area of artificial intelligence. One application of image classification that's already being used in industry is the detection of quality issues on assembly lines during manufacturing. In a typical production line, components travel down the assembly line from one station to another, at the end of which an inspector steps in to look for problems-a manual and error-prone process. AI-driven image classification reduces human effort and automatically classifies images as pass or fail. This improves not only the efficiency of the human operators in the validation process, but also the quality of the overall manufacturing process.

  Box 2: Yes

  Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found in the image. For example, if an image contains a dog, cat and person, the Detect operation will list those objects 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 object in an image.

  Box 3: No

  References:

  https://azure.microsoft.com/en-us/use-cases/defect-detection-with-image-analysis/https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

• Question 288:

  Which Computer Vision feature can you use to generate automatic captions for digital photographs?

  A. Recognize text.
  B. Identify the areas of interest.
  C. Detect objects.
  D. Describe the images.
  D. Describe the images.

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  Explanation

  Describe images with human-readable language Computer Vision can analyze an image and generate a human-readable phrase that describes its contents. The algorithm returns several descriptions based on different visual features, and each description is given a confidence score. The final output is a list of descriptions ordered from highest to lowest confidence.

  The image description feature is part of the Analyze Image API.

  References:

  https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-describing-images

• Question 289:

  DRAG DROP

  You plan to deploy an Azure Machine Learning model by using the Machine Learning designer.

  Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

  Select and Place:

  

  

• Question 290:

  You need to track multiple versions of a model that was trained by using Azure Machine Learning.

  What should you do?

  A. Provision an inference duster.
  B. Explain the model.
  C. Register the model.
  D. Register the training data.
  C. Register the model.

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  Explanation

  Register and track machine learning models With model registration, you can store and version your models in the Azure cloud, in your workspace. The model registry makes it easy to organize and keep track of your trained models.

  References:

  https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-management-and-deployment