This Week in Neo4j: Batch vs. Stream, UX Survey, Kafka Example, Jupyter/Docker for Data Science, Deep Learning
By Elaine Rosenberg
May 22, 2021 4 mins read
Hello, everyone! We at Neo4j are working to continually improve the UX experience for our users. If you have the time, please consider meeting with us to discuss your experience with our products and what you would like to see… Read more →
Explore: batch • confluent • data ingestion • data science • deep learning • docker • graph • GraphXR • JHipster • Jupyter
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 – NODES Keynote, Cypher Eager Operator, Releases of Neo4j OGM and jQAssistant
By Mark Needham
October 12, 2019 4 mins read
Our team was in Ängelholm, Sweden this week, to spend some time working together which is rare as a distributed group. But especially also to run the very first Neo4j Online Developer Conference (NODES), with more than 50 sessions by… Read more →
Explore: ann • cypher • eager • jqassistant • NODES 2019 • similarity algorithms • twin4j
This Week in Neo4j – Analyzing PostgreSQL metadata, Similarity Algorithms Deep Dive, Decision Streams
By Mark Needham
November 24, 2018 5 mins read
Welcome to This Week in Neo4j where I share the most interesting things I found in our community over the last seven days. This week I had fun with the online meetup on similarity algorithms with Tomaz Bratanic. I came… Read more →
Explore: decision stream • firebase • GraphQL • Postgres • Recommendation Engine • similarity algorithms • twin4j