Microsoft AI-102 Practice Test - Questions Answers, Page 2
List of questions
Question 11
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DRAG DROP
You train a Custom Vision model to identify a company’s products by using the Retail domain.
You plan to deploy the model as part of an app for Android phones.
You need to prepare the model for deployment.
Which three 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.
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/export-your-model
Question 12
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HOTSPOT
You are developing an application to recognize employees’ faces by using the Face Recognition API. Images of the faces will be accessible from a URI endpoint.
The application has the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/use-persondirectory
Question 13
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DRAG DROP
You have a Custom Vision resource named acvdev in a development environment.
You have a Custom Vision resource named acvprod in a production environment.
In acvdev, you build an object detection model named obj1 in a project named proj1.
You need to move obj1 to acvprod.
Which three 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.
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/copy-move-projects
Question 14
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DRAG DROP
You are developing an application that will recognize faults in components produced on a factory production line. The components are specific to your business.
You need to use the Custom Vision API to help detect common faults.
Which three 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.
Explanation:
Step 1: Create a project
Create a new project.
Step 2: Upload and tag the images
Choose training images. Then upload and tag the images.
Step 3: Train the classifier model.
Train the classifier
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier
Question 15
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HOTSPOT
You are building a model that will be used in an iOS app.
You have images of cats and dogs. Each image contains either a cat or a dog.
You need to use the Custom Vision service to detect whether the images is of a cat or a dog.
How should you configure the project in the Custom Vision portal? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Explanation:
Box 1: Classification
Incorrect Answers:
An object detection project is for detecting which objects, if any, from a set of candidates are present in an image.
Box 2: Multiclass
A multiclass classification project is for classifying images into a set of tags, or target labels. An image can be assigned to one tag only.
Incorrect Answers:
A multilabel classification project is similar, but each image can have multiple tags assigned to it.
Box 3: General
General: Optimized for a broad range of image classification tasks. If none of the other specific domains are appropriate, or if you're unsure of which domain to choose, select one of the General domains.
Reference:
https://cran.r-project.org/web/packages/AzureVision/vignettes/customvision.html
Question 16
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You are building a multilingual chatbot
You need to send a different answer for positive and negative messages.
Which two Text Analytics APIs should you use? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.
Explanation:
B: The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.
D: The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis?tabs=version-3-1
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language-detection
Question 17
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You are building a bot on a local computer by using the Microsoft Bot Framework. The bot will use an existing Language Understanding model. You need to translate the Language Understanding model locally by using the Bot Framework CU.
What should you do first?
Explanation:
You might want to manage the translation and localization for the language understanding content for your bot independently.
Translate command in the @microsoft/bf-lu library takes advantage of the Microsoft text translation API to automatically machine translate .lu files to one or more than 60+ languages supported by the Microsoft text translation cognitive service.
What is translated?
An .lu file and optionally translate
Comments in the lu file
LU reference link texts
List of .lu files under a specific path.
Reference:
https://github.com/microsoft/botframework-cli/blob/main/packages/luis/docs/translate-command.md
Question 18
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You build a conversational bot named bot1.
You need to configure the bot to use a QnA Maker application.
From the Azure Portal, where can you find the information required by bot1 to connect to the QnA Maker application?
Explanation:
Obtain values to connect your bot to the knowledge base
1. In the QnA Maker site, select your knowledge base.
2. With your knowledge base open, select the SETTINGS tab. Record the value shown for service name. This value is useful for finding your knowledge base of interest when using the QnA Maker portal interface. It's not used to connect your bot app to this knowledge base.
3. Scroll down to find Deployment details and record the following values from the Postman sample HTTP request:
4. POST /knowledgebases/<knowledge-base-id>/generateAnswer
5. Host: <your-host-url>
6. Authorization: EndpointKey <your-endpoint-key>
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-qna
Question 19
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You build a bot by using the Microsoft Bot Framework SDK and the Azure Bot Service.
You plan to deploy the bot to Azure.
You register the bot by using the Bot Channels Registration service.
Which two values are required to complete the deployment? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Explanation:
Reference:
https://github.com/MicrosoftDocs/bot-docs/blob/li ve/arti cles/bot-servi ce-qui ckstart-reqi strati on.md
Question 20
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DRAG DROP
You plan to build a chatbot to support task tracking.
You create a Language Understanding service named lu1.
You need to build a Language Understanding model to integrate into the chatbot. The solution must minimize development time to build the model. 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. (Choose four.)
Explanation:
Step 1: Add a new application
Create a new app
1. Sign in to the LUIS portal with the URL of https://www.luis.ai.
2. Select Create new app.
3. Etc.
Step 2: Add example utterances.
In order to classify an utterance, the intent needs examples of user utterances that should be classified with this intent.
Step 3: Train the application
Step 4: Publish the application
In order to receive a LUIS prediction in a chat bot or other client application, you need to publish the app to the prediction endpoint.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/tutorial-intents-only
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