Intro to Graphs and Label Propagation Algorithm in Machine Learning

[DavenH]

Oh I'm glad I found this channel. GNNs are of particular interest to me... I think there's so much potential for neural code generation.

[KhalilMuhammad]

Amazingly clear explanation. Thanks a lot!

[NoNTrvaL]

Absolutely amazing playlist! Subscribed.

[CerebroneAI]

Great visualisations, thank you for the meticulous content.

[chongtang]

I'm so luck I found this channel. Thank you!!!

[chinmayrath]

What an amazing educator. Thank you very much !!

[akritiupreti]

This makes the picture really clear. Thanks a lot!
Could you also point me to any good resources on how to readily use such a technique for a very large graphs in terms of the tech stack and packages that can be used to implement this?

[khim]

hello, appreciate your effort to make the great series of videos, and could make me clear a bit that matrix S at 6:41 is adjacency matrix, right?

[JamesSmith-dyvu]

Thanks, I'm excited for the series! I've seen something similar for label propagation done with a personalised pagerank algorithm. Do you know if there are many differences between the two?

[swakshardeb]

If we keep Y constant throughout this iterative process and initialize with random numbers for unlabeled nodes. What kind of sense does it make? Aren't we propagating wrong labels throughout the network for unlabeled nodes? Why we are not changing Y as the network keeps updating?

[jtetrfs]

What was the intro music, just before the main content starts at 1:30?

[kimminuk]

Is this, what's called, "Loopy Belief Propagation"?

[henrygengiti]

can you please clarify sigma one more time?