Graph Data Science: Networks and Graph Analytics

Graph data science analyzes relationships between entities. This lesson covers network analysis, centrality, community detection, and graph neural networks.

Graph Fundamentals

NetworkX Basics

The adjacency matrix represents graph connectivity:

Centrality Measures

Degree centrality:

Betweenness centrality:

Community Detection

Graph Algorithms

Graph Neural Networks (GNNs)

Knowledge Graphs

Graph Features for ML

Key Takeaways

1. Graphs model relationships between entities
2. Centrality measures identify important nodes
3. Community detection finds groups in networks
4. GNNs learn node/graph representations
5. Graph features enable ML on network data