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Microsoft AI-900, also known as the Microsoft Azure AI Fundamentals Exam, is a certification exam offered by Microsoft that assesses an individual's knowledge of artificial intelligence (AI) and machine learning (ML) concepts and their ability to apply them using Microsoft Azure technologies. AI-900 Exam is intended for individuals who are interested in understanding AI and ML technologies and their applications in the Azure ecosystem. The AI-900 exam is considered an entry-level certification and is a great starting point for those who want to build a career in AI and ML.
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Microsoft AI-900 Exam is an excellent way to demonstrate your knowledge and skills in the field of artificial intelligence and machine learning. Microsoft Azure AI Fundamentals certification is useful for professionals who want to pursue a career in AI or machine learning or for those who want to expand their knowledge and skills in this area. Microsoft Azure AI Fundamentals certification is also helpful for individuals who work in the IT industry and want to stay up-to-date with the latest technological advancements.
NEW QUESTION # 176
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?
Answer: C
Explanation:
Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai
NEW QUESTION # 177
Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 3: Natural language processing
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
NEW QUESTION # 178
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
NEW QUESTION # 179
You need to identify street names based on street signs in photographs.
Which type of computer vision should you use?
Answer: A
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe features of computer vision workloads on Azure", Optical Character Recognition (OCR) is a core computer vision workload that enables AI systems to detect and extract text from images or scanned documents.
In this scenario, the goal is to identify street names from street signs in photographs. Since the text is embedded within images, OCR is the correct technology to use. OCR works by analyzing the visual patterns of letters, numbers, and symbols, then converting them into machine-readable text. Azure's Computer Vision API and Azure AI Vision Service provide OCR capabilities that can extract printed or handwritten text from pictures, documents, and even real-time camera feeds.
Let's analyze the other options:
* A. Object detection: Identifies and locates objects (like cars, people, or street signs) but not the text written on them.
* C. Image classification: Classifies an entire image into categories (e.g., "street scene" or "traffic sign") but doesn't extract text content.
* D. Facial recognition: Identifies or verifies people by analyzing facial features, unrelated to text extraction.
Therefore, identifying street names on street signs is a text extraction problem, making Optical Character Recognition (OCR) the most accurate and verified answer per Microsoft Learn content.
NEW QUESTION # 180
What are two tasks that can be performed by using the Computer Vision service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation:
B: Azure's Computer Vision service provides developers with access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
C: Computer Vision includes Optical Character Recognition (OCR) capabilities. You can use the new Read API to extract printed and handwritten text from images and documents.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/home
NEW QUESTION # 181
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