Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional neural ...

Data from rotating shafts affords engineers with information needed to identify and eliminate the cause of repeated machine failure: overloads, excessive torque, side loading (from chain or belt ...

The last chart shows an actual example of a machine crash with and without mechanical overload protection. The drive in this case had a maximum torque of 28 N-m and a torque limiter adjusted to a ...

His research is on data management and machine learning for the emerging problems in large graphs. He is an IEEE senior member and an ACM distinguished speaker. Arijit is the recipient of the IBM Ph.D ...

Data science and machine learning features: Notebooks and Graph Neural Networks GQL still has some way to go. Standardization efforts are always complicated , and adoption is not guaranteed across ...

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

Graph databases hold numerous attractions for financial services users, among them the ability to detect hidden patterns in data that could be harder to spot otherwise. Some financial institutions are ...

He explained that the new service helps customers analyze existing Neptune graph data or data lakes on top of S3 storage, taking advantage of vector search to find key insights.