Use Graphs for Smarter AI with Neo4j and Google Cloud Vertex AI
By Angela Zimmerman
January 7, 2022 8 mins read
Learn how to use Neo4j AuraDB along with Google Cloud Vertex AI to build and deploy graph-based machine learning models.
Explore: ai • anti-fraud • AuraDS • Connected Data • data science • data scientists • Google Cloud • Google Cloud Vertex AI • graph database • graph embeddings
This Week in Neo4j – More on GraphQL v2, A Focus on Graph Embeddings, and Recommendation Engines with Kafka
By Clair Sullivan
August 21, 2021 5 mins read
Hello, everyone! For this week of Twin4j, we wanted to highlight a few different things. First, we get the chance to take an in-depth look at the newly-released GraphQL library 2.0.0. Next, we are dedicating most of this issue to… Read more →
Explore: Aura • FastRP • graph data science library • graph database • graph embeddings • GraphQL • GraphSAGE • Kafka • node2vec • Recommendation Engine
New Supervised Machine Learning Workflows in Neo4j!
By Enzo
February 11, 2021 5 mins read
Discover the new features in GDS 1.5, including new algorithms, more machine learning, and easier production deployment.
Explore: algorithms • data science • GDS 1.5 • GDS release • graph data science • graph embeddings • neo4j • production deployment • supervised machine learning
Evolving Your Application of GDS Technology
By Jocelyn Hoppa
December 10, 2020 8 mins read
Discover how graph data science helps you make better decisions, increase quality predictions and creat new ways to innovate and learn.
Explore: gds technology • Graph Analytics • graph data science • graph embeddings • graph feature engineering • graph networks • knowledge graphs • machine learning
Insider Guide to Graph Data Science: First, a Brief Overview
By Jocelyn Hoppa
October 12, 2020 6 mins read
Check out the first installment in this blog series on insider tips and tricks for the Neo4j Graph Data Science Library.
Explore: graph algorithms • Graph Analytics • graph data science • graph embeddings • graph export • in-memory graph • machine learning
This Week in Neo4j – Low Code GraphQL, Dagster, Executives of Belgian Public Companies Graph
By Mark Needham
July 18, 2020 4 mins read
Hi graph gang, In this week’s video, Will Lyon shows off a tool that enables a low-code approach to building GraphQL APIs. Rik Van Bruggen revisits the graph of Belgian executives, Lju Lazarevic announces the Neo4j Summer of Nodes, and… Read more →
Explore: dagster • graph data science • graph embeddings • GraphQL • low-code • OGM • summer of nodes • twin4j
Upgrade Your Graph Data Science Library Now (or Miss Out on Cool New Features)
By Jocelyn Hoppa
July 14, 2020 5 mins read
Learn about the newest features in Neo4j Graph Data Science library 1.3 released, and discover why you need to upgrade from the old algorithm library.
Explore: centrality algorithms • community detection algorithm • data science • GDS library • graph algorithms • graph data science • graph embeddings • link prediction • multi-database • pathfinding algorithms
This Week in Neo4j – Web Applications with Neo4j and TypeScript, Neo4j Desktop Release, Graph Embeddings Tutorial
By Mark Needham
July 11, 2020 4 mins read
Hi graph gang, In this week’s video, Adam Cowley starts a video showing how to build web applications with Neo4j and TypeScript. Stefan Dreverman builds a new module in the low code platform, Rik Van Bruggen explains what Fraud Detection… Read more →
Explore: fraud detection • graph data science • graph embeddings • low-code • nestjs • node2vec • spring boot • twin4j
This Week in Neo4j – Neo4j AuraDB is Here, Graph Embeddings, Graph Modeling: All about relationships, Exploring Structural Balance
By Mark Needham
November 9, 2019 4 mins read
Hi graph gang, Neo4j’s Database as a Service product had its official launch this week and it has a brand new name – Neo4j AuraDB. If you love developing graph applications but aren’t experienced operating them in production, this is… Read more →
Explore: graph data modeling • graph embeddings • GraphConnect 2020 • Neo4j Aura • Networks Crowds Markets • twin4j
How Graphs Enhance Artificial Intelligence
By Jocelyn Hoppa
September 18, 2019 12 mins read
Explore the increasing impact of graph technology on artificial intelligence and the steps toward enhancing AI and ML with a graph database.
Explore: ai • artificial intelligence • feature engineering • graph embeddings • graphconnect • knowledge graphs • machine learning • ML • native learning • neural networks
DeepWalk: Implementing Graph Embeddings in Neo4j
By Jocelyn Hoppa
September 12, 2019 12 mins read
Discover tips and strategies for implementing graph embedding into a Neo4j graph database, with plenty of Cypher examples.
Explore: artificial intelligence • community detection algorithm • deep learning • DeepWalk • graph algorithms • Graph Analytics • graph database • graph embeddings • java • machine learning