AI-102 VALID TEST SAMPLE - AI-102 VALID TEST BLUEPRINT

AI-102 Valid Test Sample - AI-102 Valid Test Blueprint

AI-102 Valid Test Sample - AI-102 Valid Test Blueprint

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Tags: AI-102 Valid Test Sample, AI-102 Valid Test Blueprint, Valid AI-102 Exam Review, AI-102 Latest Exam Duration, AI-102 Test Dates

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One of the key objectives of the Microsoft AI-102 exam is to test candidates' ability to design and implement machine learning models using Azure Machine Learning. This includes understanding how to select appropriate algorithms, prepare data for training, and fine-tune models to achieve the best possible performance. Candidates will also be tested on their ability to deploy machine learning models as web services using Azure Kubernetes Service (AKS).

Microsoft AI-102 Exam is a challenging exam, and it requires a significant amount of time and effort to prepare for it. However, with the right study materials and preparation, individuals can clear the exam with flying colors. AI-102 exam is also a great way to demonstrate your expertise in AI solutions to potential employers and clients.

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AI-102 Valid Test Blueprint - Valid AI-102 Exam Review

The web-based AI-102 practice test is accessible via any browser. This AI-102 mock exam simulates the actual Microsoft AI-102 exam and does not require any software or plugins. Compatible with iOS, Mac, Android, and Windows operating systems, it provides all the features of the desktop-based AI-102 Practice Exam software.

Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q68-Q73):

NEW QUESTION # 68
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? 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: LargeFaceListID
LargeFaceList: Add a face to a specified large face list, up to 1,000,000 faces.
Note: Given query face's faceId, to search the similar-looking faces from a faceId array, a face list or a large face list. A "faceListId" is created by FaceList - Create containing persistedFaceIds that will not expire. And a
"largeFaceListId" is created by LargeFaceList - Create containing persistedFaceIds that will also not expire.
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar


NEW QUESTION # 69
Hotspot Question
You have a bot that was built by using the Microsoft Bot Framework composer as shown in the following exhibit.

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:
https://learn.microsoft.com/en-us/composer/concept-language-understanding?tabs=v2x#entities Entities are a collection of objects, each consisting of data extracted from an utterance such as places, times, and people. Entities and intents are both important data extracted from utterances.
An utterance may include zero or more entities, while an utterance usually represents one intent.
In Composer, all entities are defined and managed inline. Entities in the .lu file format are denoted using {<entityName>=<labelled value>} notation.
https://learn.microsoft.com/en-us/composer/concept-events-and-triggers?tabs=v2x#intent-triggers


NEW QUESTION # 70
Hotspot Question
You are building an app that will automatically translate speech from English to French, German, and Spanish by using Azure AI service.
You need to define the output languages and configure the Azure AI Speech service.
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:


NEW QUESTION # 71
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? 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: LargeFaceListID
LargeFaceList: Add a face to a specified large face list, up to 1,000,000 faces.
Note: Given query face's faceId, to search the similar-looking faces from a faceId array, a face list or a large face list. A "faceListId" is created by FaceList - Create containing persistedFaceIds that will not expire. And a
"largeFaceListId" is created by LargeFaceList - Create containing persistedFaceIds that will also not expire.
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar


NEW QUESTION # 72
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are building a chatbot that will use question answering in Azure Cognitive Service for Language.
You have a PDF named Doc1.pdf that contains a product catalogue and a price list.
You upload Doc1.pdf and train the model.
During testing, users report that the chatbot responds correctly to the following question: What is the price of <product>?
The chatbot fails to respond to the following question: How much does <product> cost?
You need to ensure that the chatbot responds correctly to both questions.
Solution: From Language Studio, you create an entity for cost, and then retrain and republish the model.
Does this meet the goal?

  • A. Yes
  • B. No

Answer: B


NEW QUESTION # 73
......

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