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Microsoft.AI-900-KR.v2026-09-01.q162 모의시험 (Page 11)

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AI-900-KR 문제 46

다음과 같은 앱이 있습니다.
* App1: 종양 이미지 세트를 사용하여 종양이 양성인지 악성인지 식별하고 치료법을 제안합니다.
* App2: 농장 내에서 이동하는 개별 가축을 추적하기 위해 카메라의 이미지를 사용합니다.
* App3: 광고판 사진 속 브랜드 식별
각 앱은 무엇을 사용하나요? 답변하려면 답변 영역에서 적절한 옵션을 선택하세요.
참고: 정답 1개당 1점입니다.

정답:

Explanation:

Let's analyze each application in the context of Microsoft Azure AI Fundamentals (AI-900) and computer vision model types.
* App1 - Uses a set of images of tumors to identify whether the tumors are benign or malignant and suggest a treatment # Image classificationThis application is performing image classification, where each image (of a tumor) is assigned to a single predefined category - benign or malignant. Image classification models learn patterns from labeled training images and predict the correct class for new ones. In this case, the model identifies the type of tumor, a classic binary classification scenario.
* App2 - Uses images from cameras to track individual livestock as they move around a farm # Object detectionThis scenario describes object detection, which not only identifies what objects (in this case, animals) are in an image but also locates them by drawing bounding boxes. Tracking movement requires detecting the position of each animal frame by frame. Object detection models are well-suited for use cases involving counting, tracking, or monitoring objects in a visual scene.
* App3 - Identifies brands in photographs of billboards # Optical character recognition (OCR)This app involves reading and interpreting text (brand names, slogans, or logos) from images of billboards.
Optical Character Recognition (OCR), part of Azure AI Vision, extracts textual information from images or scanned documents. Once extracted, that text can be analyzed to identify brand names or keywords.
Summary:
* App1 # Image classification
* App2 # Object detection
* App3 # Optical character recognition (OCR)

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AI-900-KR 문제 47

특정 지역의 동물 개체수를 예측해야 합니다.
어떤 Azure Machine Learning 유형을 사용해야 합니까?

A. 클러스터링

B. 분류

C. 회귀

정답: C

According to the AI-900 official study materials, regression is a type of supervised machine learning used to predict continuous numeric values. Predicting the animal population of an area involves estimating a numeric quantity, which makes regression the appropriate model type.
Microsoft Learn defines regression workloads as predicting real-valued outputs, such as:
* Forecasting sales or demand.
* Predicting housing prices.
* Estimating resource usage or population sizes.
In contrast:
* Classification predicts discrete categories (e.g., "cat" or "dog").
* Clustering groups data into similar clusters but doesn't produce numeric predictions.
Therefore, because the task requires predicting a numerical population size, the verified answer is C.
Regression, as per Microsoft's AI-900 official guidelines.

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AI-900-KR 문제 48

어떤 두 가지 상황에서 음성 합성 솔루션을 사용할 수 있나요? 정답은 각각 완전한 해결책을 제시합니다.
참고: 정답 하나당 1점입니다.

A. 숫자 키패드를 사용하여 전화기에 입력된 신용카드 번호를 읽어주는 자동 음성

B. 뉴스 방송을 위한 라이브 자막 생성

C. 회의 오디오 녹음에서 핵심 문구 추출

D. 컴퓨터 게임에서 플레이어에게 소리 내어 말하는 AI 캐릭터

정답: A,D

According to the Microsoft Learn module "Explore speech capabilities of Azure AI" and the AI-900 Official Study Guide, speech synthesis (also known as text-to-speech) is the process of converting written text into spoken audio output. Azure's Speech service provides this functionality, allowing applications to produce human-like voices dynamically.
Let's evaluate each scenario:
* A. Automated voice that reads back a credit card number entered into a telephone keypad # YesThis is a classic text-to-speech (TTS) use case. The application converts numeric or textual input (such as a credit card number) into audio output that the caller hears. Azure Speech service can handle such voice responses in automated phone systems or IVR (Interactive Voice Response) setups.
* B. Generating live captions for a news broadcast # NoThis is a speech-to-text scenario (speech recognition), not speech synthesis. It involves converting audio speech into written text.
* C. Extracting key phrases from an audio recording of a meeting # NoThis involves speech-to-text followed by text analytics, not speech synthesis.
* D. An AI character in a computer game that speaks audibly to a player # YesThis is a direct example of speech synthesis, where the character's dialog text is converted into realistic spoken output for immersive interaction.
Therefore, based on Microsoft's AI-900 curriculum, speech synthesis is used in applications that convert text into audible speech, such as automated voice systems or interactive digital characters.

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AI-900-KR 문제 49

향후 10년 동안의 해수면을 미터 단위로 예측해야 합니다.
어떤 유형의 머신 러닝을 사용해야 합니까?

A. 분류

B. 회귀

C. 클러스터링

정답: B

In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Regression is a form of machine learning that is used to predict a numeric label based on an item ' s features.
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer
/introduction

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AI-900-KR 문제 50

Azure Al Document Intelligence의 사전 구축된 영수증 모델을 사용할 수 있는 Azure 서비스는 무엇입니까?

A. Azure AI 컴퓨터 비전

B. Azure 머신 러닝

C. Azure AI 서비스

D. Azure Al Custom Vision

정답: C

The prebuilt receipt model is part of Azure AI Document Intelligence (formerly Form Recognizer), which belongs to the broader Azure AI Services family. The prebuilt receipt model is designed to automatically extract key information such as merchant names, dates, totals, and tax amounts from receipts without requiring custom training.
Among the given options, C. Azure AI Services is correct because it encompasses all cognitive AI capabilities-vision, language, speech, and document processing. Specifically, Azure AI Document Intelligence is included within Azure AI Services and provides both prebuilt and custom models for processing invoices, receipts, business cards, and identity documents.
Options A (Computer Vision) and D (Custom Vision) are image-based services, not form-processing tools.
Option B (Azure Machine Learning) focuses on building custom predictive models, not using prebuilt document models.
Therefore, the correct answer is C. Azure AI Services, which includes the prebuilt receipt model in Document Intelligence.

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