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| Section | Weight | Objectives |
|---|---|---|
| Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Features of generative AI workloads on Azure | 20–25% | - Describe generative AI concepts - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Language - Describe capabilities of Azure Translator - Describe capabilities of Azure Speech - Identify types of NLP solutions |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Face - Describe capabilities of Azure Custom Vision - Identify types of computer vision solutions |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe machine learning pipelines - Describe automated machine learning - Describe core concepts of machine learning - Describe capabilities of Azure Machine Learning |
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NEW QUESTION # 269
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/architecture/reference-architectures/ai/conversational-bot
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-webchat-overview?view=azure-bot-service-4.0
NEW QUESTION # 270
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://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features
NEW QUESTION # 271
You are building a tool that will process images from retail stores and identify the products of competitors.
The solution will use a custom model.
Which Azure Cognitive Services service should you use?
Answer: A
Explanation:
to 300 words in Explanation:
The Custom Vision service under Azure Cognitive Services is specifically designed for image classification and object detection tasks that require a custom-trained model. According to the AI-900 official study materials, Custom Vision enables developers to "build, deploy, and improve image classifiers that recognize specific objects in images based on custom data." In this question, the goal is to build a system that processes images from retail stores and identifies products of competitors. Since these are unique products that may not be part of Microsoft's pre-trained models, a custom model must be created. The Custom Vision service allows you to upload your own labeled images (e.
g., product pictures), train a model to recognize those products, and then deploy it as an API for image recognition tasks.
Other options explained:
* B. Form Recognizer is used to extract text, key-value pairs, and tables from structured or semi- structured documents like invoices or receipts. It is not suitable for object identification.
* C. Face service detects and analyzes human faces, providing attributes like age, emotion, and facial landmarks, but cannot recognize general objects like products.
* D. Computer Vision is a general-purpose image analysis service used for tagging, OCR, and scene recognition, but it uses pre-trained models. It doesn't allow for custom product identification.
Thus, based on Microsoft's guidance, the best fit for recognizing competitor products from images using a custom-trained model is A. Custom Vision.
NEW QUESTION # 272
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
NEW QUESTION # 273
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:
NEW QUESTION # 274
......
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