ZDNet

Data meets science: Open access, code, datasets, and knowledge graphs for machine learning research and beyond

Science and data are interwoven in many ways. The scientific method has lent a good part of its overall approach and practices to data-driven analytics, software development, and data science. Now ...
ZDNet

Graph, machine learning, hype, and beyond: ArangoDB open source multi-model database releases version 3.7

If open source is the new normal in enterprise software, then that certainly holds for databases, too. In that line of thinking, Github is where it all happens. So to have been favorited 10.000 times ...
SiliconANGLE

Neo4j advances machine learning compatibility for its graph database

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 ...
dbta

TigerGraph Unveils its ML Workbench to Deliver Deep Learning and Graph Neural Network Frameworks

TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench—a powerful toolkit that enables data scientists to significantly improve ML ...
Science Daily

Not too big: Machine learning tames huge data sets

A machine-learning algorithm demonstrated the capability to process data that exceeds a computer's available memory by identifying a massive data set's key features and dividing them into manageable ...
Business Wire

Herophilus Publishes General Method for Detecting Relevant Signals in Machine Learning Analysis of Complex Biological Datasets

SAN FRANCISCO--(BUSINESS WIRE)--Herophilus, a leading biotechnology company developing neurotherapeutics to cure complex brain diseases, today announced the publication of research that describes a ...