A majority of the complex Machine Learning (ML) models lack in human interpretability. This lacking makes it difficult for human users to interpret why a particular prediction outcome has been made by ...

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 ...

Usage analysis from machine learning practitioners building real models with ModelTracker over six months shows ModelTracker is used often and throughout model building. A controlled experiment ...

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 ...

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key ...

Description: A component of Spark for graph processing and graph-structured data analytics. GraphX is Apache Spark’s library for graph analytics, providing a unified API for graph-parallel computation ...

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 ...

More information: Xiaorui Su et al, Interpretable identification of cancer genes across biological networks via ...