AI-900試験無料問題集「Microsoft Azure AI Fundamentals 認定」
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create question and answer text by using Azure Al Language Service ' s question answering? Each correct answer presents a complete solution.
NOTE: Each correct and ask questions by selection is worth one point.
What are three ways to create question and answer text by using Azure Al Language Service ' s question answering? Each correct answer presents a complete solution.
NOTE: Each correct and ask questions by selection is worth one point.
正解：A,C,D
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解説: (GoShiken メンバーにのみ表示されます)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) study guide and Azure Cognitive Services documentation, the Custom Vision service is a specialized computer vision tool that allows users to build, train, and deploy custom image classification and object detection models. It is part of the Azure Cognitive Services suite, designed for scenarios where pre-built Computer Vision models do not meet specific business requirements.
* "The Custom Vision service can be used to detect objects in an image." # YesThis statement is true.
The Custom Vision service supports object detection, enabling the model to identify and locate multiple objects within a single image using bounding boxes. For example, it can locate cars, products, or animals in photos.
* "The Custom Vision service requires that you provide your own data to train the model." # YesThis statement is true. Unlike pre-trained models such as the standard Computer Vision API, the Custom Vision service requires users to upload and label their own images. The system uses this labeled dataset to train a model specific to the user's scenario, improving accuracy for custom use cases.
* "The Custom Vision service can be used to analyze video files." # NoThis statement is false. The Custom Vision service works only with static images, not videos. To analyze video files, Azure provides Video Indexer and Azure Media Services, which are designed for extracting insights from moving visual content.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
The Azure Text Analytics service, a component of Azure Cognitive Services, provides natural language processing (NLP) capabilities to analyze and understand text-based data. According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features and uses for Natural Language Processing (NLP)", the Text Analytics service supports multiple text understanding tasks, such as language detection, key phrase extraction, sentiment analysis, and entity recognition.
* Language Identification - Yes:Text Analytics can automatically detect the language in which text is written. This feature analyzes linguistic patterns and assigns a language code (for example, "en" for English, "es" for Spanish). It is one of the primary features described in Microsoft Learn as part of the service's Language Detection API.
* Detect Handwritten Signatures - No:Detecting handwritten signatures is not a text-based NLP task.
Instead, it belongs to the computer vision domain, specifically Optical Character Recognition (OCR).
The Text Analytics service only processes digital text, not handwritten or image-based data. To detect handwriting or signatures, you would use the Computer Vision OCR API, not Text Analytics.
* Entity Recognition - Yes:The Text Analytics service can identify named entities-such as people, locations, organizations, dates, and quantities-within documents. This is known as Named Entity Recognition (NER), which helps extract structured information from unstructured text.
You have a database that contains a list of employees and their photos.
You are tagging new photos of the employees.
For each of the following statements select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
You are tagging new photos of the employees.
For each of the following statements select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
These answers are derived from the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore computer vision in Microsoft Azure." The Azure Face service, part of Azure Cognitive Services, provides advanced facial recognition capabilities including detection, verification, identification, grouping, and similarity analysis.
Let's analyze each statement:
* "The Face service can be used to group all the employees who have similar facial characteristics." # YesThe Face service supports a grouping function that automatically organizes a collection of unknown faces into groups based on visual similarity. It doesn't require labeled data; instead, it identifies clusters of similar-looking faces. This is particularly useful when building or validating datasets of people.
* "The Face service will be more accurate if you provide more sample photos of each employee from different angles." # YesAccording to Microsoft documentation, model accuracy improves when you provide multiple high-quality images of each person under different conditions-such as varying lighting, poses, and angles. This diversity allows the service to better learn unique facial characteristics and improves recognition reliability, especially for identification and verification tasks.
* "If an employee is wearing sunglasses, the Face service will always fail to recognize the employee." # NoThis is incorrect. While occlusions (like sunglasses or hats) can reduce accuracy, the service may still recognize the person depending on how much of the face remains visible. Microsoft Learn explicitly notes that partial occlusion affects recognition confidence but does not guarantee failure.
In conclusion, the Face service can group similar faces (Yes), become more accurate with diverse samples (Yes), and still recognize partially covered faces though with lower confidence (No). These principles align directly with the Face API's core functions and AI-900 learning objectives regarding computer vision and responsible AI-based facial recognition.
Select the answer that correctly completes the sentence.
正解：
Explanation:
"Optical Character Recognition (OCR) extracts text from handwritten documents." According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of computer vision workloads," Optical Character Recognition (OCR) is a computer vision capability that enables AI systems to detect and extract printed or handwritten text from images, scanned documents, and photographs.
Microsoft Learn explains that OCR uses machine learning algorithms to analyze visual data, locate regions containing text, and then convert that text into machine-readable digital format. This capability is essential for automating processes such as document digitization, form processing, and data extraction.
OCR technology is provided through services such as the Azure Cognitive Services Computer Vision API and Azure Form Recognizer. The Computer Vision API's OCR feature can extract text from both typed and handwritten sources, including receipts, invoices, letters, and forms. Once extracted, this text can be processed, searched, or stored electronically, enabling automation and efficiency in document management systems.
Let's review the incorrect options:
* Object detection identifies and locates objects in an image by drawing bounding boxes (e.g., detecting vehicles or people).
* Facial recognition identifies or verifies individuals by comparing facial features.
* Image classification assigns an image to one or more predefined categories (e.g., "dog," "car," "tree").
None of these perform the task of extracting textual content from images - that is uniquely handled by Optical Character Recognition (OCR).
Therefore, based on the AI-900 official study content, the verified and correct answer is Optical Character Recognition (OCR), as it specifically extracts text (printed or handwritten) from image-based documents.
To complete the sentence, select the appropriate option in the answer area.
正解：
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Identify features and uses of speech capabilities", speech recognition refers to the process of converting spoken words into written text. When a speaker's voice is transcribed into subtitles during a presentation, the system listens to the audio input, identifies the spoken words, and generates corresponding text in real time. This is precisely what speech recognition technology accomplishes.
Azure provides this functionality through the Azure Speech Service, which supports multiple speech-related features:
* Speech-to-Text (Speech Recognition) - Converts spoken audio into text.
* Text-to-Speech (Speech Synthesis) - Converts written text into spoken audio.
* Speech Translation - Translates spoken words into another language.
In this case, the session is transcribed into subtitles in the same language, not translated or spoken aloud, so the correct feature is Speech Recognition.
Let's review the other options:
* Sentiment Analysis: This belongs to the Text Analytics service under natural language processing (NLP) and is used to determine the emotional tone of text, not to convert speech to text.
* Speech Synthesis: Converts text into audible speech (Text-to-Speech), the reverse of what is happening in this scenario.
* Translation: Converts spoken or written words from one language to another. Here, no translation is mentioned-only transcription.
Therefore, the described process-turning live spoken language into readable subtitles-is an example of Speech Recognition, a speech-to-text AI capability provided by Azure Cognitive Services.
Final answer: Speech recognition
Reference:Microsoft Learn - Identify speech capabilities of Azure AI services (AI-900 Learning Path)