Explore the boardroom connections of the largest US companies

Neural networks have been adapted to leverage the structure and properties of graphs. We explore the components needed for building a graph neural network - and motivate the design choices behind them.

Jesús Barrasa presents the two biggest uses of ontologies in graphs using Neo4j and NeoSemantics; inferences and interoperability.

Graph theory / network library for analysis and visualisation - compatible with CommonJS/Node.js/Browserify/Webpack, AMD/Require.js, npm, Bower, jspm, Meteor/Atmosphere, jQuery, and plain JS/JavaScript

GraphQL provides a complete description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

Dijkstra's algorithm is an algorithm for finding the shortest paths between nodes in a graph, which may represent, for example, road networks.