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If you are looking to demonstrate your skills in designing and implementing Microsoft Azure AI solutions, then the Microsoft AI-102: Designing and Implementing a Microsoft Azure AI Solution exam is the right choice for you. AI-102 exam covers all the essential topics related to designing and implementing AI solutions using Azure services and tools. Passing AI-102 exam will help you earn the Microsoft Certified: Azure AI Engineer Associate certification, which is highly valued by employers and recognized globally.
To pass the Microsoft AI-102 Exam, candidates must have a deep understanding of AI fundamentals, including machine learning models, data preparation, feature engineering, and model selection. They must also have practical experience in designing and implementing AI solutions in Azure, including deploying models, monitoring performance, and troubleshooting issues.
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Microsoft AI-102 is a certification exam that is designed to test the skills of professionals in designing and implementing AI solutions on the Microsoft Azure platform. AI-102 exam is targeted towards developers, data scientists, and AI engineers who have experience working with Azure technologies and want to validate their expertise in designing and implementing AI solutions.
NEW QUESTION # 296
You need to develop an extract solution for the receipt images. The solution must meet the document processing requirements and the technical requirements.
You upload the receipt images to the From Recognizer API for analysis, and the API ret urns the following JSON.
Which expression should you use to trigger a manual review of the extracted information by a member of the Consultant-Bookkeeper group?
Answer: D
Explanation:
The requirements state:
* All AI solution responses must have a confidence score # 70%.
* If the response confidence score is < 70%, the response must be improved by human input.
* Members of the Consultant-Bookkeeper group must be able to process financial documents, which includes performing manual review when the AI confidence is below threshold.
Looking at the provided JSON:
"fields": {
"ReceiptType": {
"type": "string",
"valueString": "Itemized",
"confidence": 0.672
},
"MerchantName": {
"type": "string",
"valueString": "Tailwind",
"confidence": 0.913
}
}
* ReceiptType.confidence = 0.672 # this is below 0.7.
* MerchantName.confidence = 0.913 # this is above 0.7.
Therefore, the correct condition for triggering manual review is:
documentResults.fields.<field>.confidence < 0.7
Now, evaluating the options:
* A. documentResults.docType == "prebuilt:receipt"
* Always true for receipts, does not check confidence. Not correct.
* B. documentResults.fields.*.confidence < 0.7
* This is the correct general expression: trigger manual review whenever any field confidence is below 0.7.
* C. documentResults.fields.ReceiptType.confidence > 0.7
* This would bypass manual review when ReceiptType has high confidence. The requirement is to trigger review when confidence < 0.7, so this is the opposite.
* D. documentResults.fields.MerchantName.confidence < 0.7
* This only checks one field (MerchantName). In the JSON, MerchantName has confidence 0.913 (>0.7), so this condition would not trigger, but ReceiptType clearly needs review. Too narrow.
B). documentResults.fields.*.confidence < 0.7
* Azure AI Document Intelligence - Confidence scores
* Human-in-the-loop for Document Intelligence
Microsoft References
NEW QUESTION # 297
You have a chatbot.
You need to test the bot by using the Bot Framework Emulator. The solution must ensure that you are prompted for credentials when you sign in to the bot.
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:
NEW QUESTION # 298
You are developing the smart e-commerce project.
You need to design the skillset to include the contents of PDFs in searches.
How should you complete the skillset design diagram? To answer, drag the appropriate services to the correct stages. Each service 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:
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-concept-intro
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr
NEW QUESTION # 299
Hotspot Question
You are developing a text processing solution.
You develop the following method.
You call the method by using the following code.
GetKeyPhrases(textAnalyticsClient, "the cat sat on the mat");
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:
Box 1: Yes
The Key Phrase Extraction API evaluates unstructured text, and for each JSON document, returns a list of key phrases.
Box 2: No
'the' is not a key phrase.
This capability is useful if you need to quickly identify the main points in a collection of documents. For example, given input text "The food was delicious and there were wonderful staff", the service returns the main talking points: "food" and "wonderful staff".
Box 3: No
Key phrase extraction does not have confidence levels.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics- how-to-keyword-extraction
NEW QUESTION # 300
You have an Azure subscription.
You are building a chatbot that will use an Azure OpenAI model.
You need to deploy the model.
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:
Explanation:
You are building a chatbot that will use an Azure OpenAI model.
You need to deploy the model in your Azure subscription.
* Apply for access to Azure OpenAI
* Azure OpenAI is a gated service and requires approval before you can provision resources.
* Provision an Azure OpenAI resource
* After approval, you must provision an Azure OpenAI resource in your subscription.
* Deploy the GPT model
* Since the chatbot requires natural language understanding and conversation, you deploy a GPT model (e.g., GPT-4, GPT-3.5).
Key Steps to Deploy an Azure OpenAI Model for a Chatbot:
* Provision Azure API Management # Not needed for basic deployment (used only for advanced API management scenarios).
* Deploy the embeddings model # Used for search/RAG, not necessary for chatbot baseline.
* Deploy the DALL-E model # Used for image generation, not chatbot text responses.
Actions That Are Not Required for this Question:
* Apply for access to Azure OpenAI.
* Provision an Azure OpenAI resource.
* Deploy the GPT model.
Correct Order:
Verified Answer (Sequence):
* Apply for access to Azure OpenAI
* Provision an Azure OpenAI resource
* Deploy the GPT model
Microsoft References:
* Quickstart: Get started with Azure OpenAI
* Deploying models in Azure OpenAI
NEW QUESTION # 301
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