The big news this week for Neo4j was two major releases: Graph Data Science (GDS) 2.0 and AuraDS. GDS 2.0 brings a ton of new features, such as improvements to similarity algorithms, unified machine learning pipelines, and simplified graph projections using Cypher.
Another big highlight in this release is a native Python client that allows you to establish a connection to your database and easily call GDS procedures without having to configure a driver or manage transaction functions.
AuraDS is the new managed service for graph data science. Like AuraDB, it provides the ability to have a fully-hosted service to import, analyze, and visualize graph data. With AuraDS, data scientists can spend their time working with their data and won’t have to worry about managing infrastructure. Exciting times, to be sure!
Read all about it in the blog!
Cheers,
Clair Sullivan
FEATURED COMMUNITY MEMBER: Tomaz Bratanic
Tomaž Bratanič is a data analyst and engineer who turns everything into a graph. He is a prolific writer of blogs related to data science and the author of Graph Algorithms for Data Science from Manning Publications. A long time contributor to the Neo4j community, he has shared his expertise about graphs since 2017. Kudos to Tomaž! Follow him on Twitter.
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Don’t forget to retweet if you like it!Playing with the Egyptian football league clubs DATA ??#Egypt #Data #Neo4j pic.twitter.com/uG7DTAsD58
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