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Microsoft AI-900 Exam Syllabus Topics:

Section	Weight	Objectives
Describe features of computer vision workloads on Azure	15-20%	- Identify common computer vision tasks - Describe Azure capabilities for computer vision - Identify Azure AI services for computer vision
Describe features of Natural Language Processing (NLP) workloads on Azure	15-20%	- Identify Azure AI services for NLP - Identify common NLP tasks - Describe Azure capabilities for NLP
Describe AI workloads and considerations	15-20%	- Identify features of common AI workloads - Identify guiding principles for responsible AI
Describe features of Generative AI workloads on Azure	15-20%	- Describe generative AI concepts - Identify responsible AI considerations for generative AI - Describe Azure OpenAI Service capabilities
Describe fundamental principles of machine learning on Azure	30-35%	- Describe core machine learning concepts - Describe features of no-code automated ML - Describe Azure Machine Learning capabilities - Identify common machine learning tasks

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最新的 Microsoft Certified: Azure AI Fundamentals AI-900 免費考試真題 (Q180-Q185):

問題 #180
To complete the sentence, select the appropriate option in the answer area.

答案：

解題說明：

Explanation:
In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine learning model to predict.
In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.
Incorrect Answers:
Not features: In machine learning and statistics, feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model. Feature selection helps narrow the field of data to the most valuable inputs. Narrowing the field of data helps reduce noise and improve training performance.
Reference:
https://www.cloudfactory.com/data-labeling-guide

問題 #181
You need to determine the location of cars in an image so that you can estimate the distance between the cars.
Which type of computer vision should you use?

A. face detection
B. optical character recognition (OCR)
C. object detection
D. image classification

答案：C

解題說明：
Section: Describe features of computer vision workloads on Azure
Explanation:
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like
"indoor", which can't be localized with bounding boxes.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

問題 #182
You need to develop a mobile app for employees to scan and store their expenses while travelling.
Which type of computer vision should you use?

A. semantic segmentation
B. optical character recognition (OCR)
C. image classification
D. object detection

答案：B

解題說明：
Azure's Computer Vision API includes Optical Character Recognition (OCR) capabilities that extract printed or handwritten text from images. You can extract text from images, such as photos of license plates or containers with serial numbers, as well as from documents - invoices, bills, financial reports, articles, and more.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-recognizing-text

問題 #183
Select the answer that correctly completes the sentence.

答案：

解題說明：

Explanation:

問題 #184
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.

答案：

解題說明：

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/overview
https://docs.microsoft.com/en-us/azure/cognitive-services/face/concepts/face-detection

問題 #185
......

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