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| Section | Weight | Objectives |
|---|---|---|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
>> AI-900 Reliable Test Question <<
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NEW QUESTION # 321
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
"Optical Character Recognition (OCR) extracts text from handwritten documents." According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of computer vision workloads," Optical Character Recognition (OCR) is a computer vision capability that enables AI systems to detect and extract printed or handwritten text from images, scanned documents, and photographs.
Microsoft Learn explains that OCR uses machine learning algorithms to analyze visual data, locate regions containing text, and then convert that text into machine-readable digital format. This capability is essential for automating processes such as document digitization, form processing, and data extraction.
OCR technology is provided through services such as the Azure Cognitive Services Computer Vision API and Azure Form Recognizer. The Computer Vision API's OCR feature can extract text from both typed and handwritten sources, including receipts, invoices, letters, and forms. Once extracted, this text can be processed, searched, or stored electronically, enabling automation and efficiency in document management systems.
Let's review the incorrect options:
* Object detection identifies and locates objects in an image by drawing bounding boxes (e.g., detecting vehicles or people).
* Facial recognition identifies or verifies individuals by comparing facial features.
* Image classification assigns an image to one or more predefined categories (e.g., "dog," "car," "tree").
None of these perform the task of extracting textual content from images - that is uniquely handled by Optical Character Recognition (OCR).
Therefore, based on the AI-900 official study content, the verified and correct answer is Optical Character Recognition (OCR), as it specifically extracts text (printed or handwritten) from image-based documents.
NEW QUESTION # 322
brectly completes the sentence.
Answer:
Explanation:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Identify features of common AI workloads", OCR (Optical Character Recognition) is a Computer Vision technology that detects and extracts printed or handwritten text from images and scanned documents.
OCR allows organizations and individuals to convert physical or image-based text into machine-readable, editable, and searchable digital text.
In the context of this question, a historian working with old newspaper articles or archival documents would use OCR to digitize printed content. For instance, the historian can scan or photograph old newspaper pages, and then use an OCR tool-such as Azure Computer Vision's OCR API-to automatically recognize and extract the textual content from those images. This process enables the historian to store, edit, and analyze the content digitally without manually typing everything.
OCR works by using deep learning algorithms trained on thousands of text samples. The system analyzes patterns, shapes, and spatial relationships of characters to identify text accurately, even from low-quality or aged paper documents. Once extracted, the digital text can be indexed, translated, or processed further using Natural Language Processing (NLP) tools for content analysis.
Now, addressing the other options:
* Facial analysis is used to detect emotions, age, or gender from human faces-irrelevant to text digitization.
* Image classification identifies entire images by categories (e.g., cat, car, flower).
* Object detection identifies and locates multiple objects within an image but doesn't extract text.
Therefore, per the AI-900 learning objectives under the Computer Vision workload, the correct and verified completion is:
NEW QUESTION # 323
You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.
This is an example of which type of natural language processing workload?
Answer: C
Explanation:
Section: Describe features of Natural Language Processing (NLP) workloads on Azure Explanation:
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language- processing
NEW QUESTION # 324
A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.
You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.
This is an example of which type of machine learning?
Answer: C
Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/introduction
NEW QUESTION # 325
You are developing a chatbot solution in Azure.
Which service should you use to determine a user's intent?
Answer: D
Explanation:
Explanation
Language Understanding (LUIS) is a cloud-based API service that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.
Design your LUIS model with categories of user intentions called intents. Each intent needs examples of user utterances. Each utterance can provide data that needs to be extracted with machine-learning entities.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis
NEW QUESTION # 326
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