PASS GUARANTEED QUIZ 2025 FANTASTIC MICROSOFT AI-900: LATEST MICROSOFT AZURE AI FUNDAMENTALS TRAINING

Pass Guaranteed Quiz 2025 Fantastic Microsoft AI-900: Latest Microsoft Azure AI Fundamentals Training

Pass Guaranteed Quiz 2025 Fantastic Microsoft AI-900: Latest Microsoft Azure AI Fundamentals Training

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With the Microsoft Azure AI Fundamentals AI-900 exam, you will have the chance to update your knowledge while obtaining dependable evidence of your proficiency. You can benefit from a number of additional benefits after completing the Microsoft Azure AI Fundamentals AI-900 Certification Exam. But keep in mind that the AI-900 certification test is a worthwhile and challenging certificate.

Microsoft AI-900 certification exam is an ideal starting point for individuals who want to build a career in AI and ML. Microsoft Azure AI Fundamentals certification exam is designed to test your foundational knowledge of AI and ML concepts and how they can be applied to the Azure platform. By passing the AI-900 Exam, you will gain a better understanding of how AI and ML can be used to solve real-world problems, and you will be able to use Azure AI services and tools to build intelligent applications.

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The third and last format is the Microsoft Azure AI Fundamentals (AI-900) desktop practice test software that can be used on Windows laptops and PCs. Students with laptops or computers can access the software and prepare for it efficiently. The Microsoft Azure AI Fundamentals (AI-900) dumps of Test4Sure have many premium features, one of which is practice exams (desktop and web-based).

Microsoft Azure AI Fundamentals Sample Questions (Q211-Q216):

NEW QUESTION # 211
You send an image to a Computer Vision API and receive back the annotated image shown in the exhibit.

Which type of computer vision was used?

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

Answer: A

Explanation:
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


NEW QUESTION # 212
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing


NEW QUESTION # 213
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:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer


NEW QUESTION # 214
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:


NEW QUESTION # 215
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

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/get-started-build-detector


NEW QUESTION # 216
......

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