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| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
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NEW QUESTION # 303
You need to build an app that will identify celebrities in images.
Which service should you use?
Answer: B
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official learning path, the appropriate service for recognizing celebrities in images is Azure AI Vision (formerly Computer Vision). This service is part of Azure's Cognitive Services suite and specializes in analyzing visual content using pretrained deep learning models. One of its built-in capabilities, as documented in Microsoft Learn: "Analyze images with Azure AI Vision", includes object detection, face detection, and celebrity recognition.
The Azure AI Vision Analyze API can detect and identify thousands of objects, brands, and celebrities. When an image is submitted to the service, the model compares detected faces to a known database of public figures and returns metadata including celebrity names, confidence scores, and bounding box coordinates. This makes it ideal for applications that need to recognize well-known individuals automatically-such as media cataloging, content tagging, or entertainment apps.
The other options are incorrect:
* A. Azure OpenAI Service provides generative AI and language models (like GPT-4), but it cannot analyze image content directly in the context of AI-900 fundamentals.
* B. Azure Machine Learning is for custom model training and deployment, not a prebuilt vision recognition service.
* C. Conversational Language Understanding (CLU) processes natural language input, not images.
Therefore, the correct service for identifying celebrities in images is D. Azure AI Vision.
NEW QUESTION # 304
Which two languages can you use to write custom code for Azure Machine Learning designer? Each correct answer presents a complete solution.
NOTE; Each correct selection is worth one point.
Answer: A,D
NEW QUESTION # 305
You are developing a solution that uses the Text Analytics service.
You need to identify the main talking points in a collection of documents. Which type of natural language processing should you use?
Answer: C
Explanation:
Broad entity extraction: Identify important concepts in text, including key Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language- processing
NEW QUESTION # 306
To complete the sentence, select the appropriate option in the answer area.
Using Recency, Frequency, and Monetary (RFM) values to identify segments of a customer base is an example of___________
Answer: A
Explanation:
Classification
NEW QUESTION # 307
Match the facial recognition tasks to the appropriate questions.
To answer, drag the appropriate task from the column on the left to its question on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: verification
Face verification: Check the likelihood that two faces belong to the same person and receive a confidence score.
Box 2: similarity
Box 3: Grouping
Box 4: identification
Face detection: Detect one or more human faces along with attributes such as: age, emotion, pose, smile, and facial hair, including 27 landmarks for each face in the image.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/#features
NEW QUESTION # 308
......
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