참고자료

[JoonsunRyu]

참고 링크

Slack에 올린 여러 링크를 한번에 모아서 보자

협업/연동/세팅 관련

1. SQL sub-query 만들기: https://colab.research.google.com/github/lucasmoratof/sql-projects/blob/master/Introduction_to_SQL_sub_queries.ipynb#scrollTo=_xkGEn95uh6W

2. Colab과 Github 연동하기: https://velog.io/@shong676/Colab%EA%B3%BC-GitHub-%EC%97%B0%EB%8F%99%ED%95%98%EA%B8%B0

3. MindMeister: https://www.mindmeister.com/?utm_source=Google_Ads&utm_medium=Paid_Search&utm_campaign=WW_en_PBPQ_GA_SS_MM&gclid=Cj0KCQjwnMWkBhDLARIsAHBOftrcI2yQ6ZanNJvGXFP_dMrMRG5CBpibaIwW4B3fBb3XfJ0g0AGr9_IaAgQrEALw_wcB
   이 플랫폼은 딱히 쓰지는 않을듯

4. Jira software: https://www.atlassian.com/software/jira?&aceid=&adposition=&adgroup=140479881486&campaign=18442480203&creative=656562805651&device=c&keyword=jira&matchtype=e&network=g&placement=&ds_kids=p73335832032&ds_e=GOOGLE&ds_eid=700000001558501&ds_e1=GOOGLE&gclid=Cj0KCQjwnMWkBhDLARIsAHBOfto5Mc9rKlnFJSDU_15YlysYbzCJJ6xy2PCLQu1w2dxZmvhB1ohOs4MaAstEEALw_wcB&gclsrc=aw.ds

5. 린 캔버스: https://www.elancer.co.kr/blog/view?seq=109
   양식: https://drive.google.com/drive/folders/1_XYEitkTjgYqbZ5OaZLCzQhdMaXEbf3I

6. 구글 클라우드 저장소 -> Colab 데이터 가져오기: https://saturncloud.io/blog/how-to-import-data-from-google-cloud-storage-to-google-colab/

7. Cloud Storage FUSE를 사용한 Cloud Storage 버킷 마운트: https://cloud.google.com/storage/docs/gcsfuse-quickstart-mount-bucket

8. LLM 튜닝 프레임워크(노코드 개발툴): https://github.com/FlowiseAI/Flowise

9. 웹사이트 디자인 툴 figma: https://www.figma.com/

주제/프로젝트 관련

1. 얼굴표정인식 (Facial Expression Recognition, FER): https://paperswithcode.com/task/facial-expression-recognition/latest
   facetorch 깃허브: https://github.com/tomas-gajarsky/facetorch

2. AIhub - 당뇨관리 앱을 통한 음식 이미지 활용 및 환류: https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=71392

3. AIhub - 경구약제 이미지 데이터: https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=576

4. AIhub - 기상 정보 데이터: https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=478

5. 환경 빅데이터 플랫폼 데이터검색: https://www.bigdata-environment.kr/user/data_market/list.do

도움될 만한 정보

1. MAP(Mean Average Precision): https://towardsdatascience.com/map-mean-average-precision-might-confuse-you-5956f1bfa9e2
   https://jonathan-hui.medium.com/map-mean-average-precision-for-object-detection-45c121a31173

2. OpenCV 메뉴얼: https://opencv-python.readthedocs.io/en/latest/

3. Colab 런타임: https://research.google.com/colaboratory/local-runtimes.html

4. Object Detection 설명: https://viso.ai/deep-learning/object-detection/

5. 알약 이미지 인식 사례 (앱개발): https://libertegrace.tistory.com/entry/Milestone-Week-2-%EC%95%8C%EC%95%BD-%EB%93%B1%EB%A1%9D-%EA%B8%B0%EB%8A%A5%EC%9D%84-%EC%9C%84%ED%95%9C-%EC%95%8C%EC%95%BD-%EC%9D%B4%EB%AF%B8%EC%A7%80-%EC%9D%B8%EC%8B%9D-%EC%A4%80%EB%B9%84%EB%B0%B0%ED%8F%AC

6. SQL 코드 작성해주는 사이트: https://tableconvert.com/csv-to-sql

에러 관련

1. Github 토큰 관련: https://jonhyuk0922.tistory.com/233

2. 효율적 파이썬 코드 작성법: https://medium.com/geekculture/18-ways-to-write-better-python-1d4556b444c1

3. ML 벡엔드 최적화: https://hyperconnect.github.io/2023/05/30/Python-Performance-Tips.html