kglab
(TBD) Distributed processing with `RAPIDS` and `Ray`
DerwenAI/kglab
kglab
DerwenAI/kglab
Home
User Guide
User Guide
Overview
Getting Started
What's a Knowledge Graph?
Use Cases
Concepts
Package Reference
Dependencies
Build Instructions
Tutorial
Tutorial
Setup
Setup
Installation
Data and Ontology sources
Construction and Serialization
Construction and Serialization
Build an RDF graph using `RDFlib`
Leverage the `kglab` abstraction layer
Build a medium size KG from a CSV dataset
Querying
Querying
Run SPARQL queries
Validation
Validation
SHACL validation with `pySHACL`
Visualization
Visualization
Interactive graph visualization with `PyVis`
Graph Algorithms
Graph Algorithms
Graph algorithms with `NetworkX`
Discover community structure using `iGraph` and `leidenalg`
Inference
Inference
Inference capabilities
Measurement and inference
Statistical relational learning with `pslpython`
Embedding
Embedding
Vector embedding with `gensim`
Topology
Topology
(TBD) Evolved Shape Prediction
Distributed Systems
Distributed Systems
(TBD) Distributed processing with `RAPIDS` and `Ray`
Glossary
Bibliography
Acknowledgements
(TBD) Distributed processing with `RAPIDS` and `Ray`
this is a placeholder
Last update: 2020-12-26