AI-900 practice questions 71–80

1. Question 71 · 236 in bank

   DRAG DROP - Match the tool to the Azure Machine Learning task. To answer, drag the appropriate tool from the column on the left to its tasks on the right. Each tool may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point.

   

   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

   1. Azure portal 2. ML designer 3. Automated ML https://learn.microsoft.com/en-us/azure/machine-learning/quickstart-create-resources?view=azureml-api-2 https://learn.microsoft.com/en-us/azure/machine-learning/concept-designer?view=azureml-api-2 Azure Machine Learning designer is a drag-and-drop UI interface to build pipeline in Azure Machine Learning.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn

   

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2. Question 72 · 236 in bank

   You need to create a customer support solution to help customers access information. The solution must support email, phone, and live chat channels. Which type of Al solution should you use?

   • Amachine learning
   • Bcomputer vision
   • Cchatbot
   • Dnatural language processing (NLP)

   Show answer

   Answer: C

   Explanation

   C is the answer. https://learn.microsoft.com/en-us/power-virtual-agents/fundamentals-what-is-power-virtual-agents Power Virtual Agents lets you create powerful AI-powered chatbots for a range of requests—from providing simple answers to common questions to resolving issues requiring complex conversations. Engage with customers and employees in multiple languages across websites, mobile apps, Facebook, Microsoft Teams, or any channel supported by the Azure Bot Framework.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

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3. Question 73 · 236 in bank

   DRAG DROP - 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.

   

   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

   1. Computer vision 2. Natural language processing 3. Anomaly detection 4. Machine learning (Clustering) https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr OCR or Optical Character Recognition is also referred to as text recognition or text extraction. Machine-learning based OCR techniques allow you to extract printed or handwritten text from images, such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. The text is typically extracted as words, text lines, and paragraphs or text blocks, enabling access to digital version of the scanned text. This eliminates or significantly reduces the need for manual data entry.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   

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4. Question 74 · 236 in bank

   Predicting how many vehicles will travel across a bridge on a give day is an example of _______. Select the answer that correctly completes the sentence.

   • Aregression
   • Btranslation
   • Cclassification
   • Dclustering

   Show answer

   Answer: A

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5. Question 75 · 236 in bank

   In a machine learning model, the data that is used as inputs are called ________. Select the answer that correctly completes the sentence.

   • Adataset
   • Blabels
   • Cvariables

   Show answer

   Answer: C

   Explanation

   C is the answer. https://learn.microsoft.com/en-us/training/modules/create-regression-model-azure-machine-learning-designer/2-regression-scenarios Regression is a form of machine learning used to understand the relationships between variables to predict a desired outcome. Regression predicts a numeric label or outcome based on variables, or features. For example, an automobile sales company might use the characteristics of a car (such as engine size, number of seats, mileage, and so on) to predict its likely selling price. In this case, the characteristics of the car are the features, and the selling price is the label.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

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6. Question 76 · 236 in bank

   You run a charity event that involves posting photos of people wearing sunglasses on Twitter. You need to ensure that you only retweet photos that meet the following requirements: ✑ Include one or more faces. ✑ Contain at least one person wearing sunglasses. What should you use to analyze the images?

   • Athe Verify operation in the Face service
   • Bthe Detect operation in the Face service
   • Cthe Describe Image operation in the Computer Vision service
   • Dthe Analyze Image operation in the Computer Vision service

   Show answer

   Answer: B

   Explanation

   B is the answer. https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-identity#face-detection-and-analysis Face detection is required as a first step in all the other scenarios. The Detect API detects human faces in an image and returns the rectangle coordinates of their locations. It also returns a unique ID that represents the stored face data. This is used in later operations to identify or verify faces. Optionally, face detection can extract a set of face-related attributes, such as head pose, age, emotion, facial hair, and glasses. These attributes are general predictions, not actual classifications. Some attributes are useful to ensure that your application is getting high-quality face data when users add themselves to a Face service. For example, your application could advise users to take off their sunglasses if they're wearing sunglasses.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

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7. Question 77 · 236 in bank

   HOTSPOT - Select the answer that correctly completes the sentence.

   

   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

   RFM ( Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history - CORRECT ANSWER IS CLUSTERING

   Source: Adapted from community discussion — Pady1234

   References

   • Microsoft Learn

   

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8. Question 78 · 236 in bank

   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.

   

   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

   1. Ingest and prepare dataset 2. Split data randomly into training and validation data 3. Train model. 4. Evaluate model against validation dataset https://learn.microsoft.com/en-us/training/modules/use-automated-machine-learning/5-machine-learning-steps

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

   

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9. Question 79 · 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.

   

   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

   YYN is the answer. https://learn.microsoft.com/en-us/training/modules/create-clustering-model-azure-machine-learning-designer/2-clustering-scenarios Clustering is a form of machine learning that is used to group similar items into clusters based on their features. For example, a researcher might take measurements of penguins, and group them based on similarities in their proportions. https://learn.microsoft.com/en-us/training/modules/create-classification-model-azure-machine-learning-designer/classification-scenarios Classification is a form of machine learning that is used to predict which category, or class, an item belongs to. This machine learning technique can be applied to binary and multi-class scenarios. For example, a health clinic might use the characteristics of a patient (such as age, weight, blood pressure, and so on) to predict whether the patient is at risk of diabetes. In this case, the characteristics of the patient are the features, and the label is a binary classification of either 0 or 1, representing non-diabetic or diabetic.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn

   

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10. Question 80 · 236 in bank

    HOTSPOT - Select the answer that correctly completes the sentence.

    

    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

    References

    • Microsoft Learn

    

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AI-900 practice, question 71. 236 questions available.