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llm-twin-course
decodingai-magazine/llm-twin-course
๐ค ๐๐ฒ๐ฎ๐ฟ๐ป for ๐ณ๐ฟ๐ฒ๐ฒ how to ๐ฏ๐๐ถ๐น๐ฑ an end-to-end ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป-๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐๐๐ & ๐ฅ๐๐ ๐๐๐๐๐ฒ๐บ using ๐๐๐ ๐ข๐ฝ๐ best practices: ~ ๐ด๐ฐ๐ถ๐ณ๐ค๐ฆ ๐ค๐ฐ๐ฅ๐ฆ + 12 ๐ฉ๐ข๐ฏ๐ฅ๐ด-๐ฐ๐ฏ ๐ญ๐ฆ๐ด๐ด๐ฐ๐ฏ๐ด
โ
4.4kstars
Python
MIT
Updated: 1d ago
๐ Project at a Glance
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What's this?Learning & Resources project leveraging aws and bytewax, built with Python, open-source
Who made it?Maintained by decodingai-magazine team, 4.4Kโญ on GitHub, #502 out of 3640 in Learning & Resources
Why does it exist?In the Learning & Resources space, aws workflows faced efficiency bottlenecks. llm-twin-course was built by decodingai-magazine to address these bytewax challenges.
What can it do?Key use cases: comet-ml, course, docker
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README โ the AI handles the rest.
๐ github.com/decodingai-magazine/llm-twin-course
๐ github.com/decodingai-magazine/llm-twin-course
Topics
awsbytewaxcomet-mlcoursedockergenerative-aiinfrastructure-as-codelarge-language-modelsllmopsmachine-learning-engineeringml-system-designmlopspulumiqdrantqwakragsuperlinked