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Improving asset health and grid resilience using machine learning

AWS Machine Learning Blog

This post is co-written with Travis Bronson, and Brian L Wilkerson from Duke Energy Machine learning (ML) is transforming every industry, process, and business, but the path to success is not always straightforward. Finally, there is no labeled data available for training a supervised machine learning model.

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Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports

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We used statistical machine learning (EchoMap) and zero-shot inference using GPT. We show that statistical machine learning can map text to structured ontology and may be especially useful for small, specialized text datasets.

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6 Reasons Why Obsidian Is My Go-To App for Deep Research Projects

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Research projects can get messy fast, so having the right tool is essentialone that seamlessly connects your thoughts and ideas while being easy to

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How RAG is Transforming Metadata Management for Businesses

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Managing files and data can often feel like an uphill battle, especially when dealing with ever-growing repositories of documents, spreadsheets, and

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How to use large language models and knowledge graphs to manage enterprise data

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In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and insurance, to retail and more. A knowledge graph is a graph-based database that represents knowledge in …

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A New Look at the Semantic Web – Communications of the ACM

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From the very early days of the World Wide Web, researchers identified a need to be able to understand the semantics of the information on the Web in …