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| Section | Objectives |
|---|---|
| Topic 1: Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |
| Topic 2: Implement Natural Language Processing Solutions | - Analyze text using Azure AI Language - Implement question answering and conversational AI - Translate and interpret language using Azure AI services |
| Topic 3: Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Extract information using OCR and form recognition - Implement custom vision models |
| Topic 4: Plan and Manage an Azure AI Solution | - Select appropriate Azure AI services - Plan solution requirements and architecture - Manage security, compliance, and responsible AI |
| Topic 5: Implement Generative AI Solutions | - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions - Integrate prompt engineering techniques |
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NEW QUESTION # 420
You plan to build a chatbot to support task tracking.
You create a Conversational Language Understanding service named Iu1.
You need to build a Conversational 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.
Answer:
Explanation:
Explanation
NEW QUESTION # 421
You are building a chatbot.
You need to use the Content Moderator API to identify aggressive and sexually explicit language.
Which three settings should you configure? To answer, select the appropriate settings in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
To detect aggressive language (e.g., profanity/abuse) and sexually explicit content in text using the Content Moderator Text - Screen API:
classify = true
Enables machine-assisted text classification that returns category scores (e.g., sexually explicit/suggestive categories). This is required to identify sexual content.
language = < code > (for example, eng )
Specifies the language so profanity/abusive terms are detected correctly. The profanity detection in Text- Screen is language dependent.
autocorrect = true
Helps normalize intentionally misspelled or obfuscated words so that profanity or aggressive terms are still detected (e.g., "f@#$" # "fuck").
Other parameters in the blade are not necessary for this goal:
PII targets personal data extraction, not aggression/sexuality.
listId is for matching against custom blocklists.
Headers like Ocp-Apim-Subscription-Key and Content-Type are required to call the API, but they are not the content-analysis settings that control detection behavior asked for in this question.
Microsoft Azure AI References
Azure AI Content Moderator - Screen text API parameters (autocorrect, language, classify) and category outputs.
Azure AI Content Moderator - Text moderation concepts: profanity detection and classification categories.
NEW QUESTION # 422
You have a Custom Vision service project that performs object detection. The project uses the General domain for classification and contains a trained model.
You need to export the model for use on a network that is disconnected from the internet.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list o' actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
NEW QUESTION # 423
You are building a chatbot that will provide information to users as shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/microsoftteams/platform/task-modules-and-cards/cards/cards-reference
https://docs.microsoft.com/en-us/composer/how-to-send-cards?tabs=v1x
NEW QUESTION # 424
You are building content for a video training solution.
You need to create narration to accompany the video content. The solution must use Custom Neural Voice.
What should you use to create a custom neural voice, and which service should you use to generate the narration? To answer, select the appropriate options in the answer area.
NOTE: Each correct answer is worth one point.
Answer:
Explanation:
Explanation:
To build narration for video training content using Custom Neural Voice, we must know where each step is done:
* Creating a Custom Neural Voice
* A Custom Neural Voice is a text-to-speech (TTS) feature within Azure AI Speech.
* It allows you to create a unique, natural-sounding synthetic voice.
* The correct tool to build and configure a custom voice is the Speech Studio portal.
* Not the Language Understanding portal (LUIS), Azure portal directly, or Bot Framework Composer.
* Generating narration
* Narration requires converting written text into speech.
* This is done via the Text-to-Speech service in Azure AI Speech.
* Other options:
* Language Understanding # For intent/utterance processing, not narration.
* Speaker Recognition # For identifying/authenticating speakers, not narration.
* Speech-to-text # Converts spoken words to text (the opposite direction).
Thus:
* Custom Neural Voice # Speech Studio portal
* Narration # Text-to-speech
Correct Answers:
* Custom neural voice: The Speech Studio portal
* Narration: Text-to-speech
* Custom Neural Voice in Speech Studio
* Text-to-Speech overview
Microsoft References
NEW QUESTION # 425
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