Remove Categorization Remove Data Extraction Remove Metadata Remove ML
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Unstructured data management and governance using AWS AI/ML and analytics services

Flipboard

After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. The solution integrates data in three tiers.

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Information extraction with LLMs using Amazon SageMaker JumpStart

AWS Machine Learning Blog

SageMaker JumpStart is a machine learning (ML) hub with foundation models (FMs), built-in algorithms, and prebuilt ML solutions that you can deploy with just a few clicks. Sensitive data extraction and redaction LLMs show promise for extracting sensitive information for redaction.

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An Overview of the Top Text Annotation Tools For Natural Language Processing

John Snow Labs

Likewise, almost 80% of AI/ML projects stall at some stage before deployment. Developing a machine learning model requires a big amount of training data. Therefore, the data needs to be properly labeled/categorized for a particular use case. Also, ML and AI models need voluminous amounts of labeled data to learn from.