Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Katie Roberts, PhD, data science solution architect at Neo4j, joined DBTA's webinar, 'Solving Data Challenges with Knowledge Graphs and Context-Aware Recommendation Systems,' to explore how building ...

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 ...

Graph database maker Neo4j Inc. today introduced a version of its Aura managed service aimed at data scientists. The new offering complements an existing managed version of its core graph database ...

Neo4j for Graph Data Science combines a native graph analytics workspace and graph database with scalable graph algorithms and graph visualization for a reliable, easy-to-use experience. This ...

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 ...