AWS Machine Learning Blog

Category: Amazon Neptune

Build a cognitive search and a health knowledge graph using AWS AI services

Medical data is highly contextual and heavily multi-modal, in which each data silo is treated separately. To bridge different data, a knowledge graph-based approach integrates data across domains and helps represent the complex representation of scientific knowledge more naturally. For example, three components of major electronic health records (EHR) are diagnosis codes, primary notes, and […]

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Incorporating your enterprise knowledge graph into Amazon Kendra

For many organizations, consolidating information assets and making them available to employees when needed remains a challenge. Commonly used technology like spreadsheets, relational databases, and NoSQL databases exacerbate this issue by creating more and more unconnected, unstructured data. Knowledge graphs can provide easier access and understanding to this data by organizing this data and capturing […]

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A personalized ‘shop-by-style’ experience using PyTorch on Amazon SageMaker and Amazon Neptune

Remember the screech of the dial-up and plain-text websites? It was in that era that the Amazon.com website launched in the summer of 1995. Like the rest of the web, Amazon.com has gone through a digital experience makeover that includes slick web controls, rich media, multi-channel support, and intelligent content placement. Nonetheless, there are certain […]

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