With the new Graph Data Science Release we want to give a technical overview of the major changes and addition to the library!
0:00 Welcome & Intro
7:10 Graph Data Science 2.0
14:20 GDS Sandbox and Python Driver with Google Colab
46:35 Graph Algorithms
54:00 ML Pipelines
1:00:50 Infrastructure
1:05:00 Wrap-Up
Colab Notebook: https://colab.research.google.com/drive/1y6ubgeebGMQP7LeV6NFM8yAmcOM-6Kr1?usp=sharing
Neo4j Graph Data Science: https://development.neo4j.dev/product/graph-data-science/
Blog: https://development.neo4j.dev/blog/introducing-graph-data-science-2-0-aurads/
Graph Data Science Documentation: https://development.neo4j.dev/docs/graph-data-science/current/
Nathan Smith Blog: https://medium.com/@nsmith_piano
Tomaz Bratanic Blog: https://bratanic-tomaz.medium.com/
Graph Algorithms for Data Science: https://www.manning.com/books/graph-algorithms-for-data-science
- The new Python driver
- Projecting graphs (Change from gds.graph.create syntax, Cypher aggregations, Subgraphs)
- Algorithm changes (Reorganized similarity functions, Path finding, depth first search ML models)
- Infrastructure (AuraDS, Cluster support, Backup and restore GDS graphs and models)