Explore the intersection of graph theory and artificial intelligence in this 57-minute Devoxx conference talk. Dive into the fundamentals of graphs, their applications in data analytics, and their role in big data processing. Discover how graph structures differ from traditional relational databases and learn about powerlaw distribution in graph analytics. Examine real-world examples, including a Game of Thrones-inspired scenario, to understand graph algorithms and isomorphism. Investigate the connection between graphs and machine learning, exploring concepts such as connection features, query-based feature engineering, and graph embeddings. Gain insights into graph neural networks and their potential applications in AI. Conclude with valuable resources for further exploration of graph-based AI technologies.
Overview
Syllabus
Intro
Technology
Introduction
Artificial Intelligence
What are graphs
Examples of graph theory
Data analytics
Data structure
Relational databases
Big data
Averages
Powerlaw Distribution
Graph Analytics
Isomorphic
Game of Thrones Example
Graph Algorithms
Onramp
Examples
Graph Networks
Machine Learning
Connection Features
Example
Applications
Query Based Feature Engineering
Graph Algorithm Feature Engineering
Graph Embeddings
Graph Feature Engineering
Graph Embedding
Graph Neural Networks
Resources
Taught by
Devoxx
