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| Section | Objectives |
|---|---|
| Implement Computer Vision Solutions | - Implement custom vision models - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision |
| Plan and Manage an Azure AI Solution | - Manage security, compliance, and responsible AI - Select appropriate Azure AI services - Plan solution requirements and architecture |
| Implement Knowledge Mining and Document Intelligence | - Enrich and index data for search scenarios - Build Azure AI Search solutions - Implement document intelligence solutions |
| Implement Generative AI Solutions | - Integrate prompt engineering techniques - Build retrieval-augmented generation (RAG) solutions - Implement Azure OpenAI Service solutions |
| Implement Natural Language Processing Solutions | - Implement question answering and conversational AI - Analyze text using Azure AI Language - Translate and interpret language using Azure AI services |
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NEW QUESTION # 303
You are building a chatbot by using the Microsoft Bot Framework SDK.
You use an object named UserProfile to store user profile information and an object named ConversationData to store information related to a conversation.
You create the following state accessors to store both objects in state.
var userStateAccessors = _userState.CreateProperty<UserProfile>(nameof(UserProfile)); var conversationStateAccessors = _conversationState.CreateProperty<ConversationData>(nameof(ConversationData)); The state storage mechanism is set to Memory Storage.
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/bot-service/bot-builder-howto-v4-state
NEW QUESTION # 304
You have a custom Azure OpenAI model.
You have the files shown in the following table.
You need to prepare training data for the model by using the OpenAI CLI data preparation tool. Which files can you upload to the tool?
Answer: E
Explanation:
You need to prepare training data for Azure OpenAI custom model fine-tuning using the OpenAI CLI data preparation tool.
* Supported input formats: JSONL (primary).
* CLI pre-processing accepted formats: TSV, CSV, JSON.
* Not supported: PDF, XML, XLSX directly.
Checking files:
* File1.tsv (80 MB) # Supported (CLI can convert TSV to JSONL).
* File2.xml (25 MB) # Not supported (XML not accepted).
* File3.pdf (50 MB) # Not supported.
* File4.xlsx (200 MB) # Not supported directly.
The answer: A. File1.tsv only
NEW QUESTION # 305
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 # 306
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 # 307
You are developing a solution to generate a word cloud based on the reviews of a company's products.
Which Text Analytics REST API endpoint should you use?
Answer: B
Explanation:
The key phrases provide us with the important words from our customer comments, not just the most common words. Also, word sizing in the resulting cloud isn't skewed by the frequent use of a word in a relatively small number of comments.
https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/key-phrase- extraction/tutorials/integrate-power-bi#create-the-word-cloud
NEW QUESTION # 308
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