Download Microsoft.AI-102.VCEplus.2021-05-04.54q.tqb
| Vendor: | Microsoft |
| Exam Code: | AI-102 |
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution (beta) |
| Date: | May 04, 2021 |
| File Size: | 7 MB |
Demo Questions
Question 1
You have 100 chatbots that each has its own Language Understanding model.
Frequently, you must add the same phrases to each model.
You need to programmatically update the Language Understanding models to include the new phrases.
How should you complete the code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct answer: To work with this question, an Exam Simulator is required.
Explanation:
Box 1: AddPhraseListAsync Example: Add phraselist feature var phraselistId = await client.Features.AddPhraseListAsync(appId, versionId, new PhraselistCreateObject { EnabledForAllModels = false, IsExchangeable = true, Name = "QuantityPhraselist", Phrases = "few,more,extra" }); Box 2: PhraselistCreateObject Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/luis/client-libraries-rest-api Box 1: AddPhraseListAsync
Example: Add phraselist feature var phraselistId = await client.Features.AddPhraseListAsync(appId, versionId, new PhraselistCreateObject
{
EnabledForAllModels = false,
IsExchangeable = true,
Name = "QuantityPhraselist",
Phrases = "few,more,extra"
});
Box 2: PhraselistCreateObject
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/client-libraries-rest-api
Question 2
You plan to use a Language Understanding application named app1 that is deployed to a container.
App1 was developed by using a Language Understanding authoring resource named lu1.
App1 has the versions shown in the following table.
You need to create a container that uses the latest deployable version of app1.
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. (Choose three.)
Correct answer: To work with this question, an Exam Simulator is required.
Explanation:
Step 1: Export the model using the Export for containers (GZIP) option. Export versioned app's package from LUIS portal The versioned app's package is available from the Versions list page. Sign on to the LUIS portal. Select the app in the list. Select Manage in the app's navigation bar. Select Versions in the left navigation bar. Select the checkbox to the left of the version name in the list. Select the Export item from the contextual toolbar above the list. Select Export for container (GZIP). The package is downloaded from the browser. Step 2: Select v1.1 of app1. A trained or published app packaged as a mounted input to the container with its associated App ID. Step 3: Run a contain and mount the model file. Run the container, with the required input mount and billing settings. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto Step 1: Export the model using the Export for containers (GZIP) option.
Export versioned app's package from LUIS portal
The versioned app's package is available from the Versions list page.
- Sign on to the LUIS portal.
- Select the app in the list.
- Select Manage in the app's navigation bar.
- Select Versions in the left navigation bar.
- Select the checkbox to the left of the version name in the list.
- Select the Export item from the contextual toolbar above the list.
- Select Export for container (GZIP).
- The package is downloaded from the browser.
Step 2: Select v1.1 of app1.
A trained or published app packaged as a mounted input to the container with its associated App ID.
Step 3: Run a contain and mount the model file.
Run the container, with the required input mount and billing settings.
Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto
Question 3
You need to build a chatbot that meets the following requirements:
- Supports chit-chat, knowledge base, and multilingual models
- Performs sentiment analysis on user messages
- Selects the best language model automatically
What should you integrate into the chatbot?
- QnA Maker, Language Understanding, and Dispatch
- Translator, Speech, and Dispatch
- Language Understanding, Text Analytics, and QnA Maker
- Text Analytics, Translator, and Dispatch
Correct answer: C
Explanation:
Language Understanding: An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language. QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information. Text Analytics: Mine insights in unstructured text using natural language processing (NLP)—no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. The Language Detection feature of the Azure Text Analytics REST API evaluates text input Incorrect Answers: A, B, D: Dispatch uses sample utterances for each of your bot’s different tasks (LUIS, QnA Maker, or custom), and builds a model that can be used to properly route your user’s request to the right task, even across multiple bots. Reference: https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/ https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/overview Language Understanding: An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language.
QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information.
Text Analytics: Mine insights in unstructured text using natural language processing (NLP)—no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. The Language Detection feature of the Azure Text Analytics REST API evaluates text input
Incorrect Answers:
A, B, D: Dispatch uses sample utterances for each of your bot’s different tasks (LUIS, QnA Maker, or custom), and builds a model that can be used to properly route your user’s request to the right task, even across multiple bots.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/overview
