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
This course includes
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
Course Content
About the Course
Introduction to Graph Theory
Graph Embeddings
Supervised and Unsupervised Graph ML
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
Appendix
1 Lesson
How You'll Learn
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