Videos

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://neo4j.com/product/graph-data-science/ Blog: https://neo4j.com/blog/introducing-graph-data-science-2-0-aurads/ Graph Data Science Documentation: https://neo4j.com/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)