Back in January, we previewed Neo4j AuraDS and Google Cloud Vertex AI’s partnership and demonstrated how you can build and deploy graph-based machine learning models. AuraDS is graph data science as a service now running as a managed service on top of GCP.
With the Neo4j Graph Data Science platform, you can easily use graph structure to compute algorithms or create embeddings and increase the accuracy and reliability of machine learning pipelines. The worked example from the blog stores data in AuraDS, and computes graph embeddings with FastRP to feed into the Vertex AI workflow.
If you’re interested in getting started on Google Cloud Vertex AI with AuraDS, this blog is for you.
Cheers,
Yolande Poirier
P.S.: We’d like to understand how you, developers, are building GraphQL APIs with managed cloud services. If you have used a GraphQL managed service, we’d love to learn about your experience and how it could be improved in this survey.
FEATURED COMMUNITY MEMBER: Gabriel Tardif
Gabriel Tardif has been using Neo4j for the past two years to manage real estate data. He joined the Ninja program and has been helping others as he ramps up his own skills in Cypher and the Neo4j platform. He is now focusing on improving his query tuning, operator, APOC, and algorithm knowledge.
Gabriel is always ready to lend a hand to his fellow nodes. Big kudos to Gabriel! Find him on the community website.
CHEATSHEET: Cypher
A decent cheatsheet can make life a lot easier. This one is a veritable dictionary that you can bookmark for future reference. All major Cypher commands are helpfully organized into functional categories and are accessible through a menu in the margin.GRAPH DATA SCIENCE ON GOOGLE CLOUD: Neo4j AuraDS and Vertex AI
It’s easy to get started on Google Cloud Vertex AI with Neo4j AuraDS. The example in this blog stores data in AuraDS, and computes graph embeddings with FastRP to feed into the Vertex AI workflow.GRAPHCONNECT: Keynotes
GraphConnect was just last week! Now you can watch the recorded keynote presentations. Keep an eye on this playlist – more session recordings will be made available over the coming weeks.
GRAPH ANALYTICS: Determining Important Nodes in a Graph Using Neo4j
In the third blog of his series, Mehul Gupta queries his database with centrality algorithms to rank nodes based on importance.GOING META: A Series On Graphs, Semantics, and Knowledge
Explore how semantics applies to property graphs in this hands-on series with Jesús Barrasa. Each episode has a wealth of information about Cypher and Sparql, semantic search, SHACL, and much more.
FOR BEGINNERS: Working with Graph Databases and Neo4j
Beren Erchamion takes his first steps with graph databases and sets up Neo4j Community Server on his MacBook Pro.TWEET OF THE WEEK: @rotnroll666
Don’t forget to retweet if you like it!Here’s a graphy Duke. have a beautiful day, #Java community. My colleagues at @Neo4j build this https://t.co/kjbiIlIMXy and I totally love it. pic.twitter.com/NpXD9N6532
— Michael Simons (@rotnroll666) June 9, 2022
