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Introduction To Graph Machine Learning

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

7h

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.

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This course includes

63 Playgrounds
7 Quizzes

This course includes

63 Playgrounds
7 Quizzes
Course Overview
What You'll Learn
Course Content

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

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Course Content

1

About the Course

Getting Started
2

Introduction to Graph Theory

What is a Graph?
Types of GraphsHow to Represent Graphs as Data StructuresGraph Network VisualizationQuiz: Graph Theory
3

Graph Embeddings

What are Graph Embeddings?Matrix Factorization-Based ApproachRandom Walk-Based ApproachNeural Network-Based ApproachQuiz: Graph Embeddings
4

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
5

Graph Neural Networks

What are Graph Neural Networks?Neural Message PassingTypes of Graph Neural NetworksQuiz: Graph Neural Networks
6

Knowledge Graph

5 Lessons

7

Knowledge Graph Embeddings

4 Lessons

8

Case Study: Link Prediction on a Social Network Graph

3 Lessons

9

Case Study: Node Classification on a Biological Graph

3 Lessons

10

Appendix

1 Lesson

Course Author

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