Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.1 - Why Graphs

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Bu1w3n Jure Leskovec Computer Science, PhD Graphs are a general language for describing and analyzing entities with relations/interactions. There are many types of networks and graphs, such as social networks, communication and transaction networks, biomedine networks, brain networks, etc. In this course, we will take advantage of relational structure for better prediction. To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224w/ Chapters: 0:00 Intro 00:05 Welcome to Machine Learning with Graphs 03:29 Natural Graphs or Networks 04:16 Relational Structure 07:24 How do we develop neural networks that are applicable to complex data types like graphs? 10:06 Traditional methods for machine learning and graphics - graphlets and graph kernels 11:24 Outline for the course