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| Section | Objectives |
|---|---|
| Topic 1: Implement Knowledge Mining and Document Intelligence | - Build Azure AI Search solutions - Enrich and index data for search scenarios - Implement document intelligence solutions |
| Topic 2: Implement Generative AI Solutions | - Build retrieval-augmented generation (RAG) solutions - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions |
| Topic 3: Plan and Manage an Azure AI Solution | - Select appropriate Azure AI services - Plan solution requirements and architecture - Manage security, compliance, and responsible AI |
| Topic 4: Implement Computer Vision Solutions | - Implement custom vision models - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision |
| Topic 5: Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Implement question answering and conversational AI - Analyze text using Azure AI Language |
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NEW QUESTION # 395
In Azure Al Studio, you use Completions playground with the GPT-35 Turbo model.
You have a prompt that contains the following code.
You need the model to create an explanation of the code. The solution must minimize costs. What should you do?
Answer: B
Explanation:
* You're using GPT-3.5-Turbo in Completions playground.
* You want the model to explain the given code.
* The best approach is to directly add an instruction in the prompt (e.g., // what does function F do?).
* This minimizes cost because:
* You don't need to upgrade to GPT-4 (more expensive).
* You don't need special formatting like function F(explanation).
* Changing temperature only affects randomness, not clarity of explanation.
Microsoft Reference:
Prompt engineering with GPT models
NEW QUESTION # 396
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.
Answer:
Explanation:
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
NEW QUESTION # 397
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.
Answer:
Explanation:
Explanation
Graphical user interface, text, application, email Description automatically generated
Box 1: Classification
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.
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
NEW QUESTION # 398
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:
NEW QUESTION # 399
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.
Answer:
Explanation:
1 - Create a project
2 - Upload and tag the images
3 - Train the classifier model.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier
NEW QUESTION # 400
......
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