Microsoft Azure AI Fundamentals AI-900 Practice Question
A company has amassed a vast repository of documents, including PDFs, Word files, and scanned images of text. They want to enable employees to find specific information within these documents, such as policy details or client data, regardless of the file format.
Which type of AI workload would best address this need?
Knowledge Mining is the appropriate AI workload for this scenario because it involves extracting insights from large volumes of unstructured data across various formats. It combines techniques like optical character recognition (OCR) to read text from images, natural language processing to understand the content, and search indexing to make information easily discoverable.
Natural Language Processing (NLP) focuses on understanding and generating human language but doesn't inherently handle the integration of various document types.
Computer Vision is primarily concerned with understanding visual content in images and videos, not extracting textual information from documents.
Content personalization is about tailoring user experiences based on preferences and behaviors, which doesn't address the need to search and retrieve information from a document repository.
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Microsoft Azure AI Fundamentals AI-900
Describe Artificial Intelligence Workloads and Considerations
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