# Case 02

사람별로 나누기

- [01. LLM 지도](https://slashpage.com/llm-ai-application-study-2024/xjqy1g2vqg5gpm6vd54z)
- [10. 임베딩 모델로 데이터 의미 압축하기](https://slashpage.com/llm-ai-application-study-2024/91kwev26nj3k62y46jpg)
- [02. LLM 중추, 트래스포머 아키텍처 살펴보기](https://slashpage.com/llm-ai-application-study-2024/3p4kj92y5v63y257q1x8)
- [03. 트랜스포머 모델을 다루기 위한 허킹페이스 트랜스포머 라이브러리](https://slashpage.com/llm-ai-application-study-2024/d367nxm34prde2j98pv1)
- [04. 말 잘 듣는 모델 만들기](https://slashpage.com/llm-ai-application-study-2024/n5w9812gx35xqm4kpgze)
- [05. GPU 효율적인 학습](https://slashpage.com/llm-ai-application-study-2024/4z7pvx2k9639y2ek8653)
- [06. sLLM 학습하기](https://slashpage.com/llm-ai-application-study-2024/4w67rj24ne3jx25yq8ep)
- [07. 모델 가볍게 만들기](https://slashpage.com/llm-ai-application-study-2024/qpv5x42783vgzmkyn3dw)
- [08. sLLM 서빙하기](https://slashpage.com/llm-ai-application-study-2024/91kwev26njygq2y46jpg)
- [09. LLM 애플리케이션 개발하기](https://slashpage.com/llm-ai-application-study-2024/ndvwx728nky7723z6jpg)
- [11. 자신의 데이터에 맞춘 임베딩 모델 만들기: RAG 개선하기](https://slashpage.com/llm-ai-application-study-2024/dwy5rvmj134wn2p46zn9)
- [12. 벡터데이터베이스로 확장하기: RAG 구현하기](https://slashpage.com/llm-ai-application-study-2024/ndvwx728nkrgq23z6jpg)
- [13. LLM 운영하기](https://slashpage.com/llm-ai-application-study-2024/943zqpmqz1k442wnvy87)
- [14. 멀티 모달 LLM이란](https://slashpage.com/llm-ai-application-study-2024/3p4kj92y5v8e1257q1x8)
- [15. LLM 에이전트](https://slashpage.com/llm-ai-application-study-2024/ndvwx728nkrq523z6jpg)
- [16. 새로운 아키텍처](https://slashpage.com/llm-ai-application-study-2024/n5w9812gx3z48m4kpgze)
- [17. 부록](https://slashpage.com/llm-ai-application-study-2024/93nzyxmd4gzn7mwk6r45)

For the site tree, see the [root Markdown](https://slashpage.com/llm-ai-application-study-2024.md).