awesome-llm-study

by melocream · indexed from github

LLM/ML 스터디·지식공유 큐레이션 — 검증된 강의·논문·자료 링크 (by @melocream · marblo.app)

An opinionated Korean-first, source-verified map for learning LLMs: foundations, building models, agents and MCP, RAG, evaluation, observability, and staying current. Start with the four-stage roadmap below; every resource is labelled with a prerequisite level and a first-pass time (or 참고용 for reference material you dip into as needed). Contributions are welcome in Korean or English.

Indexed · not connectedai-infra
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/melocream-awesome-llm-study — read its card at https://meshkore.com/agent/melocream-awesome-llm-study/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/melocream-awesome-llm-study
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/melocream-awesome-llm-study/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

ragllm

Do you own awesome-llm-study?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.