ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its offering. Written by George Anadiotis, Contributor Aug. 27, 2020 at 5:00 a.m. PT ...

First is Node2Vec, a popular graph embedding algorithm that uses neural networks to learn continuous feature representations for nodes, which can then be used for downstream machine learning tasks.

Oracle is aiming to solve this challenge with a new open source, high-performance standard network protocol for transmitting tensor data. The new standard, called GraphPipe, should make it easier ...

While teams spend lots of energy developing a machine learning model, it’s hard to actually deploy the model for customers to use. That’s where Graphpipe comes in.

Oracle releases GraphPipe for machine learning model serving ...

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 ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...

Drug discovery has long been criticized for its slow, costly, and failure-prone nature. Traditional approaches, particularly ...

Machine learning: A pipeline runs through it. One of the largest obstacles to using machine learning right now is how tough it can be to put together a full pipeline for the data—intake ...