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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 Natural Language Processing Solutions | - Implement question answering and conversational AI - Translate and interpret language using Azure AI services - Analyze text using Azure AI Language |
| 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 | - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions - Integrate prompt engineering techniques |
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NEW QUESTION # 159
You are examining the Azure AI Language service output of an application.
The text analyzed is: "Our tour guide took us up the Space Needle during our trip to Seattle last week." The response contains the data shown in the following table.
Which Azure AI Language service API is used to analyze the text?
Answer: A
Explanation:
Named Entity Recognition (NER) is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The NER feature can identify and categorize entities in unstructured text. For example: people, places, organizations, and quantities.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/named-entity- recognition/overview
NEW QUESTION # 160
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 161
You are using a Language Understanding service to handle natural language input from the users of a web-based customer agent.
The users report that the agent frequently responds with the following generic response: "Sorry, I don't understand that." You need to improve the ability of the agent to respond to requests.
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.)
Answer:
Explanation:
Explanation
- enable active learning
- validate the utterances
- train and republish
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-prebuilt-model
NEW QUESTION # 162
Hotspot Question
You are developing an application that will use the Azure AI 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:
Reference:
https://learn.microsoft.com/en-us/rest/api/computervision/analyze-image-in-stream/analyze-image-in-stream
NEW QUESTION # 163
You create a knowledge store for Azure Cognitive Search by using the following JSON.
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:
Explanation:
1. Number of Projection Groups
A projection group in a knowledge store is an array of projections ( tables , objects , or files ) that are stored together.
In the provided JSON, the projections array contains the following two top-level sections:
The array of tables :
JSON
" tables " : [
{ ... },
{ ... }
]
The array of objects :
JSON
" objects " : [
{ ... }
]
Each of these top-level arrays ( tables and objects ) represents a distinct projection group in the knowledge store. Therefore, there are two projection groups .
2. Image Saving
The files projection is used to save images, normalized images, or application files generated during the enrichment process.
In the provided JSON, the files array is present but is empty :
JSON
" files " : []
Since there are no file projections defined, the images (or any files) generated during the enrichment process will not be saved to the knowledge store. They are processed in the pipeline but not persisted in the output storage defined by the knowledgeStore configuration.
NEW QUESTION # 164
......
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