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Graph-Powered Analytics and Machine Learning with TigerGraph
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Graph-Powered Analytics and Machine Learning with TigerGraph
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Graph-Powered Analytics and Machine Learning with TigerGraph
1. Graph-Powered Machine Learning Methods
Unsupervised Learning with Graph Algorithms
Finding Communities
Finding Similar Things
Finding Frequent Patterns
Summary
Extracting Graph Features
Domain-Independent Features
Domain-Dependent Features
Graph Embeddings: A Whole New World
Summary
Graph Neural Networks
Graph Convolutional Networks
GraphSAGE
Summary
Comparing Graph Machine Learning Approaches
Use Cases for Machine Learning Tasks
Graph-based Learning Methods for Machine Learning Tasks
Graph Neural Networks: Summary and Uses
Chapter Summary
2. Entity Resolution Revisited
Goal: Identify Real-World Users and Their Tastes
Solution Design
Implementation
Starter Kit
Graph Model
Data Loading
Queries and Analytics
Method 1: Jaccard Similarity
Method 2: Scoring Exact and Approximate Matches
Chapter Summary
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