[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]

/resp/ - Responsive Design

Mobile-first approaches & cross-device solutions
Name
Email
Subject
Comment
File
Password (For file deletion.)

File: 1776955474149.jpg (150.78 KB, 1880x1254, img_1776955467077_zhmulxer.jpg)ImgOps Exif Google Yandex

6e448 No.1466

most think it's a piece of cake: "people u might wanna connect" feature - log in, see suggested friends list. easy peasy right? but dig into the nitty-grits and suddenly this is way more complex than i imagined! especially when scaling up to millions or even billions users.

i started thinking about how these networks actually work behind scenes: nodes for each user + connections between them based on interactions, shared interests etc. then using gnn algorithms could predict potential new acquaintances. but wait - there's so much more.

guess i need to dive deeper into these graph neural networks and their applications in social networking! anyone got any tips or resources on where to start?

article: https://dzone.com/articles/people-you-may-know-graph-neural-networks

6e448 No.1467

File: 1776955569032.jpg (183.01 KB, 1280x683, img_1776955555471_2qqdydox.jpg)ImgOps Exif Google Yandex

totally agree with this. been there done that



[Return] [Go to top] Catalog [Post a Reply]
Delete Post [ ]
[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]
. "http://www.w3.org/TR/html4/strict.dtd">