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The Best Pdf AI-102 Files offer you accurate Practice Engine | Microsoft Designing and Implementing a Microsoft Azure AI Solution
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The AI-102 Exam is intended for professionals who are responsible for designing and implementing AI solutions that use Azure services. AI-102 exam is ideal for developers, architects, and data scientists who are interested in expanding their AI skills and knowledge. AI-102 exam covers a variety of topics, including designing AI solutions, implementing AI workflows, creating and deploying machine learning models, and integrating AI solutions with other Azure services.
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.
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Another important objective of the Microsoft AI-102 Exam is to test candidates' knowledge of natural language processing (NLP) and computer vision. This includes understanding how to build custom models for tasks such as sentiment analysis, language translation, and image recognition. Candidates will also be tested on their ability to deploy these models using Azure Cognitive Services.
Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q203-Q208):
NEW QUESTION # 203
You have a chatbot that uses a QnA Maker application.
You enable active learning for the knowledge base used by the QnA Maker application.
You need to integrate user input into 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
Graphical user interface, application Description automatically generated
Step 1: For the knowledge base, select Show active learning suggestions.
In order to see the suggested questions, on the Edit knowledge base page, select View Options, then select Show active learning suggestions.
Step 2: Approve and reject suggestions.
Each QnA pair suggests the new question alternatives with a check mark, , to accept the question or an x to reject the suggestions. Select the check mark to add the question.
Step 3: Save and train the knowledge base.
Select Save and Train to save the changes to the knowledge base.
Step 4: Publish the knowledge base.
Select Publish to allow the changes to be available from the GenerateAnswer API.
When 5 or more similar queries are clustered, every 30 minutes, QnA Maker suggests the alternate questions for you to accept or reject.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base
NEW QUESTION # 204
You are building an app by using the Speech SDK. The app will translate speech from French to German by using natural language processing.
You need to define the source language and the output language.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 205
You are examining the 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 Language service API is used 10 analyze the Text?
- A. Named Entity Recognition
- B. Key Phrase Extraction
- C. Sentiment Analysis
- D. Entity Linking
Answer: A
NEW QUESTION # 206
You are building a Language Understanding model for purchasing tickets.
You have the following utterance for an intent named PurchaseAndSendTickets.
Purchase [2 audit business] tickets to [Paris] [next Monday] and send tickets to [email@domain.com] You need to select the entity types. The solution must use built-in entity types to minimize training data whenever possible.
Which entity type should you use for each label? To answer, drag the appropriate entity types to the correct labels. Each entity type 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.
Answer:
Explanation:
Explanation
Graphical user interface, application Description automatically generated
Box 1: GeographyV2
The prebuilt geographyV2 entity detects places. Because this entity is already trained, you do not need to add example utterances containing GeographyV2 to the application intents.
Box 2: Email
Email prebuilt entity for a LUIS app: Email extraction includes the entire email address from an utterance.
Because this entity is already trained, you do not need to add example utterances containing email to the application intents.
Box 3: Machine learned
The machine-learning entity is the preferred entity for building LUIS applications.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-geographyv2
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-email
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/reference-entity-machine-learned-entity
NEW QUESTION # 207
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 208
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