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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.

Microsoft AI-102 Certification Exam is a valuable credential for individuals seeking to demonstrate their proficiency in designing and implementing AI solutions on the Microsoft Azure platform. With a strong understanding of AI and machine learning concepts, as well as practical experience working on real-world projects, candidates can prepare for and pass the exam with confidence.

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Microsoft AI-102 is an exam that is designed for IT professionals who are interested in Microsoft Azure and artificial intelligence technologies. The purpose of AI-102 exam is to test the candidate's knowledge and skills in designing and implementing an AI solution using Microsoft Azure technologies. AI-102 Exam is a part of the Microsoft Certified: Azure AI Engineer Associate certification.

Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q363-Q368):

NEW QUESTION # 363
You are building a Language Understanding model for an e-commerce platform. You need to construct an entity to capture billing addresses.
Which entity type should you use for the billing address?

A. machine learned
B. geographyV2
C. Pattern.any
D. list
E. Regex

Answer: E

Explanation:
Explanation
A regular expression entity extracts an entity based on a regular expression pattern you provide. It ignores case and ignores cultural variant. Regular expression is best for structured text or a predefined sequence of alphanumeric values that are expected in a certain format. For example:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-entity-types

NEW QUESTION # 364
You are developing the knowledgebase by using Azure Cognitive Search.
You need to build a skill that will be used by indexers.
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
Box 1: "categories": ["Locations", "Persons", "Organizations"],
Locations, Persons, Organizations are in the outputs.
Scenario: Contoso plans to develop a searchable knowledgebase of all the intellectual property Note: The categories parameter is an array of categories that should be extracted. Possible category types:
"Person", "Location", "Organization", "Quantity", "Datetime", "URL", "Email". If no category is provided, all types are returned.
Box 2: {"name": " entities"}
The include wikis, so should include entities in the outputs.
Note: entities is an array of complex types that contains rich information about the entities extracted from text, with the following fields name (the actual entity name. This represents a "normalized" form) wikipediaId wikipediaLanguage wikipediaUrl (a link to Wikipedia page for the entity) etc.
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition

NEW QUESTION # 365
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

NEW QUESTION # 366
You are building a Chatbot by using the Microsoft Bot Framework SDK. The bot will be used to accept food orders from customers and allow the customers to customize each food item. You need to configure the bot to ask the user for additional input based on the type of item ordered. The solution must minimize development effort. Which two types of dialogs should you use? Each correct answer presents part of the solution. NOTE:
Each correct selection is worth one point.

A. input
B. action
C. prompt
D. adaptive
E. waterfall

Answer: C,E

Explanation:
* In the Bot Framework SDK, if you want to collect structured input step by step, you typically use a Waterfall dialog. Each step in the waterfall represents one piece of logic, such as asking for the size, toppings, or type of food item.
* Prompts are used inside waterfall steps to actually ask the user for input (e.g., text prompt, choice prompt, date-time prompt).
* Adaptive, Action, Input are concepts more relevant to Power Virtual Agents or Adaptive Dialogs (Composer), not the Bot Framework SDK question context.
* Since the question specifically mentions Bot Framework SDK, the correct answer is Waterfall dialog + Prompts.
The answer: C, D

NEW QUESTION # 367
You are developing a photo application that will find photos of a person based on a sample image by using the Face API.
You need to create a POST request to find the photos.
How should you complete the 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: findsimilars
https://docs.microsoft.com/en-us/rest/api/faceapi/face/find-similar
Box 2: matchPerson
Find similar has two working modes, "matchPerson" and "matchFace". "matchPerson" is the default mode that it tries to find faces of the same person as possible by using internal same-person thresholds. It is useful to find a known person's other photos. Note that an empty list will be returned if no faces pass the internal thresholds.
"matchFace" mode ignores same-person thresholds and returns ranked similar faces anyway, even the similarity is low. It can be used in the cases like searching celebrity-looking faces.
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/detectwithurl
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar

NEW QUESTION # 368
......

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