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

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