Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.3 - Choice of Graph Representation
106.3 هزار بار بازدید -
3 سال پیش
-
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Jure Leskovec
Computer Science, PhD
One essential task to consider before we conduct machine learning on graphs is to find an appropriate way to represent the graphs. What are the factors that will affect our choices as to the representations? In this video, we’ll be looking at the different approaches to abstracting graphs: directed vs. undirected, weighted vs. unweighted, homogeneous vs bipartite, and so on.
To follow along with the course schedule and syllabus, visit:
http://web.stanford.edu/class/cs224w/
Jure Leskovec
Computer Science, PhD
One essential task to consider before we conduct machine learning on graphs is to find an appropriate way to represent the graphs. What are the factors that will affect our choices as to the representations? In this video, we’ll be looking at the different approaches to abstracting graphs: directed vs. undirected, weighted vs. unweighted, homogeneous vs bipartite, and so on.
To follow along with the course schedule and syllabus, visit:
http://web.stanford.edu/class/cs224w/
3 سال پیش
در تاریخ 1400/01/24 منتشر شده
است.
106,331
بـار بازدید شده