Introduction to Graph Machine Learning

This introductory course provides a detailed and lucid explanation of various concepts in Graph Machine Learning, along with coding examples wherever necessary.

Beginner

37 Lessons

Certificate of Completion

This introductory course provides a detailed and lucid explanation of various concepts in Graph Machine Learning, along with coding examples wherever necessary.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

63 Playgrounds

7 Quizzes

This course includes

63 Playgrounds

7 Quizzes

Course Overview

Are you ready to attain mastery in graph machine learning? Graphs are ubiquitous and have diverse applications in various fields. In this introductory course, you will learn the fundamentals of graph machine learning so that you’re able to work with different types of graphs, state-of-the-art graph machine learning techniques, and various graph analytics tasks. The course begins with the basics of graphs and gradually progresses to more advanced topics, including graph embedding and its different technique...Show More

TAKEAWAY SKILLS

Python

Pytorch Basics

Graph

Machine Learning

What You'll Learn

Familiarity with creating and manipulating graphs

An understanding of the concepts of graph embedding and its various techniques

Ability to formulate important graph analytics tasks such as node classification and link prediction

Hands-on experience developing graph neural networks using PyTorch Geometric

An understanding of knowledge graphs and different ways to generate their embeddings

Comprehensive knowledge of graph machine learning concepts

What You'll Learn

Familiarity with creating and manipulating graphs

Course Content

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

5 Lessons

Knowledge Graph Embeddings

4 Lessons

Case Study: Link Prediction on a Social Network Graph

3 Lessons

Case Study: Node Classification on a Biological Graph

3 Lessons

10.

Appendix

1 Lesson

Course Author

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Emma Bostian 🐞

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Evan Dunbar

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Anthony Walker

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Emma Bostian 🐞

@EmmaBostian

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