차이

문서의 선택한 두 판 사이의 차이를 보여줍니다.

--- activity:public:reference:how_we_study_deep_learning [2022/08/09 08:36:00] – 몇가지 강좌 및 CS 강좌 추가 jshackist
+++ activity:public:reference:how_we_study_deep_learning [2022/08/11 03:03:14] (현재) – jshackist
@@ 줄 14: / 줄 14: @@
 [[https://datascienceschool.net/02%20mathematics/00.00%20%EC%86%8C%EA%B0%9C%EC%9D%98%20%EA%B8%80.html|데이터 사이언스 스쿨 수학 편]]
 [[https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/index.html|Dive to Deep Learning : Appendix]]
@@ 줄 21: / 줄 22: @@
 [[https://www.khanacademy.org/math/multivariable-calculus|다변수 미적분학]]
 [[http://www.kocw.net/home/cview.do?cid=7c789810ade43386|기초통계학]]
 [[http://www.kocw.net/home/cview.do?cid=7c789810ade43386|수리통계학1]]
 [[http://www.kocw.net/home/cview.do?cid=d112ad1ca7f5fda9|수리통계학2]]
-[[https://www.edwith.org/ai152|확률론]]
 [[https://www.edwith.org/ai251|선형대수학]]
@@ 줄 39: / 줄 43: @@
 [[https://iseulbee.com/archives/the-art-of-analysis-4ed/|맛있는 해석학]]
 [[https://iseulbee.com/archives/the-art-of-analysis-4ed-solution/|맛있는 해석학 문제풀이]]
+아래는 Convex Optimization에 관한 자료입니다.
+[[https://convex-optimization-for-all.github.io/|모두를 위한 컨벡스 최적화]]
+아래는 각종 수학 주제를 다루는 채널입니다. 재생목록이 잘 정비되어있는 편입니다. 수학이 즐거운 지는 솔직히 잘 모르겠습니다.
+[[https://www.youtube.com/channel/UCB_AbuIVIG8I3K3_T_j0FSw/playlists|수학의 즐거움]]
 ==== Machine Learning & Deep Learning ====
@@ 줄 51: / 줄 63: @@
 [[https://www.coursera.org/specializations/machine-learning-introduction?action=enroll&adgroupid=131088411058&adpostion=&authMode=signup&campaignid=15277156238&creativeid=561886531168&device=c&devicemodel=&gclid=CjwKCAjwwo-WBhAMEiwAV4dybbg5_Ba1kIwFxBQk-gvS1Svffn1O3FfdoRiR3uCYb3UDN7n7I8cU4RoC6VcQAvD_BwE&hide_mobile_promo=&keyword=coursera+machine+learning&matchtype=b&network=g&utm_campaign=28-MLOps-DL.ai-APAC&utm_content=B2C&utm_medium=sem&utm_source=gg|Andrew Ng's Machine Learning]]
+아래 또한 전공 수준 기계학습 강의입니다. 다루는 내용을 보면 학부 수준은 아닌 것 같습니다.
+[[https://www.edwith.org/machinelearning1_17|인공지능 및 기계학습 1]]
+[[https://www.edwith.org/machinelearning2__17|인공지능 및 기계학습 2]]
+[[https://www.edwith.org/aiml-adv|인공지능 및 기계학습 심화]]
+\\
 다음은 컴퓨터비전 Task를 해결하기 위한 목적의 딥러닝 강의입니다.
@@ 줄 75: / 줄 97: @@
 [[https://www.youtube.com/watch?v=JAB_plj2rbA&list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn&ab_channel=StanfordOnline|Machine Learning with Graphs]]
+\\
+아래는 교수님들의 재생목록입니다.
+[[https://www.youtube.com/channel/UCro6IqfE5NOspKCDusilfmw/playlists|김승룡 교수님]]
+[[https://www.youtube.com/channel/UCsEQc1-iFbu_yHvMd1vqwFQ/playlists?view=1&sort=dd&shelf_id=0|주재걸 교수님]]
 ==== Further ====
@@ 줄 89: / 줄 119: @@
 [[https://www.notion.so/c3b3474d18ef4304b23ea360367a5137?v=5d763ad5773f44eb950f49de7d7671bd|DBSA notion]]
 [[https://www.facebook.com/bigdatastudy/photos/%EB%AC%B4%EB%A3%8C-%EA%B3%B5%EC%9C%A0%EA%B3%A0%EB%A0%A4%EB%8C%80%ED%95%99%EA%B5%90-%EC%82%B0%EC%97%85%EA%B2%BD%EC%98%81%EA%B3%B5%ED%95%99%EB%B6%80-data-science-business-analytics-%EC%97%B0%EA%B5%AC%EC%8B%A4-%EC%8B%A0%EC%9E%85%EC%83%9D%EB%93%A4%EC%9D%84-%EB%8C%80%EC%83%81%EC%9C%BC%EB%A1%9C-%EB%B0%98%EB%93%9C%EC%8B%9C-%EC%9D%BD%EC%96%B4%EC%95%BC-%ED%95%98%EB%8A%94-%EB%85%BC%EB%AC%B8-/188218132667114/|논문 로드맵]]
@@ 줄 96: / 줄 127: @@
 [[https://www.youtube.com/playlist?list=PLetSlH8YjIfUpPbSAfsY4zBJfztlH9CSQ|DBSA 1]]
 [[https://www.youtube.com/playlist?list=PLetSlH8YjIfUi6p0wdA6z2dFbXUpLor6K|DBSA 2]]
 [[https://www.youtube.com/playlist?list=PLRx0vPvlEmdADpce8aoBhNnDaaHQN1Typ|나동빈 논문 리뷰]]
@@ 줄 104: / 줄 137: @@
 [[https://www.youtube.com/watch?v=auKdde7Anr8&list=PLWKf9beHi3Tg50UoyTe6rIm20sVQOH1br&ab_channel=SungKim|PR12 Season 1]]
 [[https://www.youtube.com/watch?v=FfBp6xJqZVA&list=PLWKf9beHi3TgstcIn8K6dI_85_ppAxzB8&ab_channel=MinGukKang|PR12 Season 2]]
 [[https://www.youtube.com/watch?v=D-baIgejA4M&list=PL_skMddDjnzq1wDI3t2cH9hlK6wBBapeA&ab_channel=Jiyang%27sMLPaperReview|PR12 Season 3]]
 [[https://www.youtube.com/watch?v=az-OV47oKvA&list=PL0o99tZwBlrMV3QsZ4O79KjMHDhAJpAdW&ab_channel=DoyupLee|PR12 Season 4]]
@@ 줄 141: / 줄 177: @@
 [[https://www.edwith.org/datastructure-2019s]]
 [[https://www.edwith.org/datastructure-2019s2]]