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Introduction to Graph Machine Learning

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About the Course

Getting Started

Introduction to Graph Theory

What is a Graph?Types of Graphs How to Represent Graphs as Data Structures Graph Network Visualization Quiz: Graph Theory

Graph Embeddings

What are Graph Embeddings?Matrix Factorization-Based Approach Random Walk-Based Approach Neural Network-Based Approach Quiz: Graph Embeddings

Supervised and Unsupervised Graph ML

What's Next After Learning Embeddings?Node Classification (Supervised)Link Prediction (Supervised)Graph Classification (Supervised)Graph Clustering and Community Detection (Unsupervised)Quiz: Graph Machine Learning Tasks

Graph Neural Networks

What are Graph Neural Networks?Neural Message Passing Types of Graph Neural Networks Quiz: Graph Neural Networks

Knowledge Graph

What is a Knowledge Graph?

Knowledge Graph Construction

Importance of Knowledge Graphs and Their Issues

Knowledge Graph Embeddings

Quiz: Knowledge Graphs

Knowledge Graph Embeddings

Translation-Based Methods

Factorization-Based Methods

Neural Network-Based Methods

Quiz: Knowledge Graph Embeddings

Case Study: Link Prediction on a Social Network Graph

Problem Description Approach to the Problem Coding the Solution

Case Study: Node Classification on a Biological Graph

Problem Description Approach to the Problem Coding the Solution

Appendix

Python Libraries

Quiz: Knowledge Graph Embeddings

Test your understanding of the knowledge graph embedding concepts.

1

(True or False) Translation-based embedding algorithms work on the formula $h + t = r$ .

A)

True

B)

False

Question 1 of 50 attempted

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