AI-102 Relevant Answers & AI-102 Exam Sample Online
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Microsoft AI-102 is an essential exam for professionals looking to demonstrate their expertise in designing and implementing Azure AI solutions. With the growing importance of AI in today's business environment, passing AI-102 Exam can prove to be a valuable asset for anyone looking to advance their career in this field.
AI-102 Exam Sample Online & AI-102 Latest Dumps Questions
Just download the Designing and Implementing a Microsoft Azure AI Solution (AI-102) PDF dumps file and start the Microsoft AI-102 exam questions preparation right now. Whereas the other two Designing and Implementing a Microsoft Azure AI Solution (AI-102) practice test software is concerned, both are the mock Designing and Implementing a Microsoft Azure AI Solution (AI-102) exam dumps and help you to provide the real-time Designing and Implementing a Microsoft Azure AI Solution (AI-102) exam environment for preparation.
Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q315-Q320):
NEW QUESTION # 315
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.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/use-persondirectory
NEW QUESTION # 316
You are developing an application that includes language translation.
The application will translate text retrieved by using a function named getTextToBeTranslated. The text can be in one of many languages. The content of the text must remain within the Americas Azure geography.
You need to develop code to translate the text to a single language.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
You are building an application that:
Uses Azure Translator service to translate text.
The text comes from getTextToBeTranslated() .
The text can be in many languages.
Requirement: the content must remain within the Americas Azure geography.
Output: must translate text into a single language (English in this case).
Step 1 - Choosing the correct endpoint
The Translator service provides region-specific endpoints.
For Americas geography, you must use the North America (NAM) endpoint:
https: //api-nam.cognitive.microsofttranslator.com/translate
Other options like api-apc (Asia Pacific) or api-nam.../detect are incorrect because:
/detect is used to identify the source language, not translate.
/transliterate is for script conversion, not translation.
We need the /translate path.
Step 2 - Setting the correct query parameter
To specify the target language, you must use the to query string parameter. Example:
?t o=en
Options like from=en or suggestedFrom=en are not correct here, because:
The text can be in many languages # we don't know the source language in advance.
Translator automatically detects the source if from is not specified.
We only need to define the target language.
Final Code Snippet (corrected)
var endpoint = " https://api-nam.cognitive.microsofttranslator.com/translate " ; var apiKey = " YOUR_SUBSCRIPTION_KEY " ; var text = getTextToBeTranslated(); var body = " [{ ' Text ' : ' " + text + " ' }] " ; var client = new HttpClient(); client.DefaultRequestHeaders.Add( " Ocp-Apim-Subscription-Key " , apiKey); var uri = endpoint + " ?to=en " ; HttpResponseMessage response; var content = new StringContent(body, Encoding.UTF8, " application/json " ); response = await client.PutAsync(uri, content); Correct Answer Endpoint: https://api-nam.cognitive.microsofttranslator.com/translate URI: ?to=en Microsoft References Translator v3.0 Reference Region-specific Translator endpoints
NEW QUESTION # 317
You are developing an application that will use the Computer Vision client library. 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.
Answer:
Explanation:
Explanation:
The code will perform face recognition # No
The code will list tags and their associated confidence # Yes
The code will read a file from the local file system # Yes
The given method uses the Computer Vision client library:
* It specifies the features:
* List<VisualFeatureTypes> features = new List<VisualFeatureTypes>()
* {
* VisualFeatureTypes.Description,
* VisualFeatureTypes.Tags,
* };
That means it will return descriptions (captions) and tags from the image.
* The image is opened from the local file system:
* using (Stream imageStream = File.OpenRead(localImage))
* The analysis call:
* ImageAnalysis results = await client.AnalyzeImageInStreamAsync(imageStream, features);
* It prints captions and tags with their confidence values.
* "The code will perform face recognition."
* No.
* The requested features are Description and Tags, not Faces.
* Face recognition would require VisualFeatureTypes.Faces.
* "The code will list tags and their associated confidence."
* Yes.
* The foreach (var tag in results.Tags) loop outputs tag name and confidence.
* "The code will read a file from the local file system."
* Yes.
* It uses File.OpenRead(localImage) which reads from disk.
Statement Analysis
* The code will perform face recognition # No
* The code will list tags and their associated confidence # Yes
* The code will read a file from the local file system # Yes
Final Answer
* Analyze an image with the Computer Vision API
* VisualFeatureTypes enum reference
Microsoft References
NEW QUESTION # 318
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are building a chatbot that will use question answering in Azure Cognitive Service for Language.
You have a PDF named Doc1.pdf that contains a product catalogue and a price list You upload Doc1.pdf and train the model.
During testing, users report that the chatbot responds correctly to the following question: What is the price of
< product > ?
The chatbot fails to respond to the following question: How much does < product > cost?
You need to ensure that the chatbot responds correctly to both questions.
Solution: From Language Studio, you add alternative phrasing to the question and answer pair, and then retrain and republish the model.
Does this meet the goal?
- A. Yes
- B. No
Answer: A
Explanation:
In Question Answering (Custom question answering in Azure AI Language), you improve coverage for different user phrasings by adding alternative questions to the same answer. For example, adding "How much does < product > cost?" as an alternate question to the existing Q/A about "What is the price of < product > ?" enables the service to match both user queries to the same answer. After adding alternates, you must retrain and republish the project for changes to take effect. This directly addresses the gap and meets the goal.
References
Add and manage alternative questions in custom question answering; retrain/republish for updates.
https://learn.microsoft.com/azure/ai-services/language-service/question-answering/how-to/contribute-to- project Custom question answering concepts and authoring workflow.
https://learn.microsoft.com/azure/ai-services/language-service/question-answering/overview
NEW QUESTION # 319
You need to measure the public perception of your brand on social media messages. Which Azure Cognitive Services service should you use?
- A. Form Recognizer
- B. Text Analytics
- C. Computer Vision
- D. Content Moderator
Answer: B
Explanation:
Text Analytics Cognitive Service could be used to quickly determine the public perception for a specific topic, event or brand.
Example: A NodeJS app which pulls Tweets from Twitter using the Twitter API based on a specified search term. Then pass these onto Text Analytics for sentiment scoring before storing the data and building a visualisation in PowerBI. The Architecture looked something like this:
Reference:
https://www.linkedin.com/pulse/measuring-public-perception-azure-cognitive-services-steve-dalai
NEW QUESTION # 320
......
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