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Microsoft AI-900 Exam, also known as the Microsoft Azure AI Fundamentals exam, is a certification exam that tests individuals on their knowledge of artificial intelligence and its applications in Microsoft Azure. AI-900 exam is designed for individuals who are interested in learning about AI and its practical use in the cloud, and for those who are looking to gain a basic understanding of AI terminology, concepts and technologies.

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Microsoft Azure AI Fundamentals Sample Questions (Q241-Q246):

NEW QUESTION # 241
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://developers.google.com/machine-learning/practica/image-classification
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-model-builder
https://nanonets.com/blog/how-to-do-semantic-segmentation-using-deep-learning/


NEW QUESTION # 242
Which Computer Vision feature can you use to generate automatic captions for digital photographs?

Answer: A

Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Describe features of computer vision workloads on Azure," the "Describe Image" feature within Azure's Computer Vision service automatically generates textual captions that describe the contents of an image.
This feature uses a deep learning model trained on millions of labeled images to identify objects, people, and scenes, then formulates a natural language sentence summarizing what it sees. For example, given a photograph showing "two people sitting at a table with a laptop," the service might generate the caption: "A man and a woman sitting at a desk using a laptop." Here's how the other options differ:
* A. Recognize text: Refers to Optical Character Recognition (OCR), which extracts written text from images, not generates descriptive captions.
* C. Identify the areas of interest: Refers to detecting regions of an image that stand out visually, such as hotspots or significant features, not descriptive captioning.
* D. Detect objects: Identifies and classifies objects in an image (e.g., cars, chairs, people) but doesn't produce a sentence or caption summarizing them.
Thus, only "Describe the images" generates automatic, human-readable captions that summarize photo content, a core computer vision workload taught in AI-900.


NEW QUESTION # 243
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/


NEW QUESTION # 244
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:


NEW QUESTION # 245
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

The Text Analytics API is a cloud-based service that provides advanced natural language processing over raw text, and includes four main functions: sentiment analysis, key phrase extraction, named entity recognition, and language detection.
Box 1: Yes
You can detect which language the input text is written in and report a single language code for every document submitted on the request in a wide range of languages, variants, dialects, and some regional/cultural languages. The language code is paired with a score indicating the strength of the score.
Box 2: No
Box 3: Yes
Named Entity Recognition: Identify and categorize entities in your text as people, places, organizations, date/time, quantities, percentages, currencies, and more. Well-known entities are also recognized and linked to more information on the web.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview


NEW QUESTION # 246
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