Top videos
#ZeroToDeployment
Building awesome apps from scratch completely open source.
Download on Playstore: https://play.google.com/store/....apps/details?id=com.
GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning
✅ Equipment I use and recommend:
https://www.amazon.com/shop/aladdinpersson
❤️ Become a Channel Member:
https://www.youtube.com/channe....l/UCkzW5JSFwvKRjXABI
✅ One-Time Donations:
Paypal: https://bit.ly/3buoRYH
Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc
▶️ You Can Connect with me on:
Twitter - https://twitter.com/aladdinpersson
LinkedIn - https://www.linkedin.com/in/al....addin-persson-a95384
PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf
👋 CONNECT WITH ME:
Twitter ► https://twitter.com/aladdinperzon
LinkedIn ► https://www.linkedin.com/in/al....addin-persson-a95384
GitHub ► https://github.com/aladdinpersson
PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf
TensorFlow Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf
Using Python to Play Cyberpunk 2077 through computer vision.
Sample code: https://github.com/Sentdex/cyberpython2077
Series Playlist: https://www.youtube.com/playli....st?list=PLQVvvaa0QuD
Channel membership: https://www.youtube.com/channe....l/UCfzlCWGWYyIQ0aLC5
Discord: https://discord.gg/sentdex
Support the content: https://pythonprogramming.net/support-donate/
Twitter: https://twitter.com/sentdex
Instagram: https://instagram.com/sentdex
Facebook: https://www.facebook.com/pythonprogramming.net/
Twitch: https://www.twitch.tv/sentdex
Resources that was very useful for me when learning about GNNs that you can check out for more information and from which I've used in the slides:
Cs224w: https://youtube.com/playlist?l....ist=PLoROMvodv4rPLKx
https://distill.pub/2021/gnn-intro/
https://distill.pub/2021/understanding-gnns/
https://www.youtube.com/playli....st?list=PLV8yxwGOxvv
https://youtu.be/8owQBFAHw7E
https://youtu.be/uF53xsT7mjc
https://youtu.be/w6Pw4MOzMuo
0:00 Introduction
1:24 Why graphs
4:13 What is a graph
7:06 Common graph tasks
11:08 Representation of a graph
12:46 - How does a GNN work?
14:35 - Understanding information propagation
17:24 - Key property: Permutation Invariance
19:33 - Key property: Permutation Equivariance
22:22 - Message passing computation
23:53 - GNN Variant: Convolution
26:37 - GNN Variant: Attention
28:39 - Ending