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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Describe fundamental principles of machine learning on Azure | 30-35% | - Describe features of no-code automated ML - Identify common machine learning tasks - Describe Azure Machine Learning capabilities - Describe core machine learning concepts |
| Topic 3: Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Identify Azure AI services for NLP - Describe Azure capabilities for NLP |
| Topic 4: Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
| Topic 5: 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 |
Students are given a fixed amount of time to complete each test, thus Microsoft Exam Questions candidate's ability to control their time and finish the Microsoft Azure AI Fundamentals (AI-900) exam in the allocated time is a crucial qualification. Obviously, this calls for lots of practice. Taking Prep4pass AI-900 Practice Exam helps you get familiar with the Microsoft Azure AI Fundamentals (AI-900) exam questions and work on your time management skills in preparation for the real Microsoft Azure AI Fundamentals (AI-900) exam.
NEW QUESTION # 53
You need to build an app that will identify celebrities in images.
Which service should you use?
Answer: D
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 # 54
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-science-process/create-features
NEW QUESTION # 55
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer
NEW QUESTION # 56
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.
Answer:
Explanation:
1 - data preparation
2 - model tranining
3 - model evaluation
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines
NEW QUESTION # 57
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud.
Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/
NEW QUESTION # 58
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