Notebook Tutorials

• Getting Started
  • For analysts
  • For developers
  • CSV upload miniapp
  • Visually analyze any table as a graph: Our 3 favorite shapings
• Visualization
  • Encodings
  • Layout
  • Accounts and Sharing
• GFQL Graph queries
  • 1. Install & configure
  • 2. Load & enrich a US congress twitter interaction dataset
  • 3. Simple filtering: g.hop() & g.gfql([...])
  • 3. Simple filtering: g.hop() & g.gfql([...])
  • 4. Multi-hop and paths-between-nodes pattern mining
  • 4. Multi-hop and paths-between-nodes pattern mining
  • 5. Advanced filter predicates
  • 6. Result labeling
  • 7. Pattern Reuse with Let Bindings
  • GFQL Validation Fundamentals
  • DateTime Filtering Examples
  • GPU Benchmarking
  • GFQL Remote mode
  • Python Remote mode
• GPU
  • GPU I: CPU Pandas
  • GPU II: cuDF
  • GPU IV: cuML UMAP
  • GPU V: cuGraph
  • How much GPU RAM do you need and how much data fits into a GPU task?
  • Phase 1: Setup and Data Creation
• AI
  • Story
  • RGCN
  • RGCN+UMAP
  • Link prediction with DGL (cyber)
• Plugins - Data Providers
  • AlienVault: OTX indicators
  • AlienVault: Locker Goga
  • AlientVault: USM
  • Amazon Neptune I
  • Amazon Neptune II
  • Arango
  • Databricks
  • Memgraph
  • Tutorial: Using Azure Data Explorer’s Persistent Graphs with Kusto & Graphistry
  • Graph Visualization
  • NodeXL
  • Splunk
  • Titan
  • Neo4j - Official
  • Neo4j - Contributed
  • Google Spanner - Finance Graph
  • SQL - Postgres
  • Tigergraph: Bindings
  • Tigergraph: Fraud
  • Tigergraph: Social
• Plugins - Compute & Layout
  • graphviz
  • HyperNetX
  • NetworkX