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.

Graph data science is an emerging field with a lot of promise, but it’s being hamstrung by the need for practitioners to have lots of data engineering and ETL skills. Now Neo4j is hoping to drive that ...

SAN MATEO, Calif. – April 8th, 2020 – Neo4j, the leader in graph technology, announced the availability of Neo4j for Graph Data Science, the first data science environment built to harness the ...

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 ...

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 ...

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 ...

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 ...

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.

Neo4j Graph Data Science aims to help build complex towers of logically constructed data ...More relationships.. Adrian Bridgwater. Data is everywhere, all the time.