Book Content
chapters • 9h36m total length
1. Introducing and Installing Neo4j
2. Using Existing Data to Build a Knowledge Graph
3. Characterizing a Graph Dataset
4. Using Graph Algorithms to Characterize a Graph Dataset
5. Visualizing Graph Data
6. Building a Machine Learning Model with Graph Features
7. Automatically Extracting Features with Graph Embeddings for Machine Learning
8. Building a GDS Pipeline for Node Classification Model Training
9. Predicting Future Edges
10. Writing Your Custom Graph Algorithm with the Pregel API
