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.

Neo4j Graph Data Science makes it easy for data scientists to work within their existing data pipeline of tools across their ecosystem. Data scientists can use Neo4j Graph Data Science on-premises, ...

Neo4j for Graph Data Science was conceived for this purpose, to improve the predictive accuracy of machine learning, or answer previously unanswerable analytics questions, using the relationships ...

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 ...

Network graphs, now growing in popularity, are designed to help us see connections, ... Investing in your data science team’s graph skill development will also help.

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 ...

Digital Science has completed the acquisition of metaphacts, which has become the newest member of the Digital Science family. Based in Germany, metaphacts is a knowledge graph and decision ...

Graphs are among the most widely-used data structures in machine learning. Their power comes from the flexibility of capturing relations (edges) of collections of entities (nodes) which arise in a ...

The Michigan Tech Data Science MS provides a broad-based education in data mining, predictive analytics, cloud computing, data-science fundamentals, ... tree and graph visualization, large-scale data ...