This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...

SVM and kNN exemplify several important trade-offs in machine learning (ML). SVM is often less computationally demanding than kNN and is easier to interpret, but it can identify only a limited set ...

Combining graphs and machine learning has been getting a lot of attention lately, especially since the work published by researchers from DeepMind, Google Brain, MIT, and the University of Edinburgh.

Amazon Neptune just added another query language, openCypher, to its arsenal. That may not sound like a big deal in and of itself, but coupled with updates in machine learning and data science ...

TigerGraph, maker of a graph analytics platform for data scientists, during its Graph & AI Summit event today introduced its TigerGraph ML (Machine Learning) Workbench, a new-gen toolkit that ...

Her research focuses on developing innovative algorithms and models that push the boundaries of machine learning, optimization, and artificial intelligence. Subscribe To Newsletters 7:08 ...