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The Three Main Use Cases for a Graph Database

datastax

There’s a reason smart organizations are increasingly moving to graph databases : the modern technology delivers the scalability, performance, and agility today’s most powerful applications require. But how, specifically, can you use graph data to improve your operations and ultimately your bottom line? Customer 360.

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Build a GNN-based real-time fraud detection solution using Amazon SageMaker, Amazon Neptune, and the Deep Graph Library

AWS Machine Learning

Many techniques have been used to detect fraudsters—rule-based filters, anomaly detection, and machine learning (ML) models, to name a few. Such a graph structure can provide valuable information for anomaly detection. Recently, graph neural network (GNN) has become a popular method for fraud detection.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. The solution is agnostic to use cases, which means you can adapt it for your use cases by changing the model and data. HCLS use case. In the first post , we described FL concepts and the FedML framework. patientunitstayid.

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Link Building, CTR, and Data Driven Agency – Client Relationships

Grade.us

The agency itself has been recognized all over the world for what it's accomplished by gathering data and using that data both to strategize and to innovate for clients. You build tools, you use smart ways of running spreadsheets to surface these insights. I used to get up on stages at many conferences and say, " Link building is dead.

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