CS231N_17_KOR_SUB
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CS231N 2017 video subtitles translation project for Korean Computer Science students
Korean Subtitles for CS231n Spring 2017
CS231n 한글번역
Translation project of CS231n 2017 lecture video
Also see CS231n Website
Announcements
CS231n 한글번역 프로젝트입니다. Stanford의 CS231n는 CNN(Convolutional Neural Network)을 중심으로 Deep Learning을 배우는 현존하는 가장 좋은 강의 중 하나. 이 프로젝트는 CS231n을 수강하기에 언어의 장벽으로 힘든 분들을 위한 한글 번역 프로젝트입니다. 많은 분들이 이 강의를 듣고 행복했으면 좋겠습니다. 하지만 CS231n 정도의 수준 그리고 그 이상을 위해서라면 영어실력이 뒷받침해 줘야 하는 것은 명백한 사실입니다.
도올 김용옥 선생의 "영어 수학을 왜 공부해야 하는가?
> CS231n에 의 대상
1) Deep Learning을 처음 접하는 초급자
2) Deep Learning을 어느정도 알지만 심도깊게 배우고 싶은 중급자
3) Deep Learning의 트렌드를 살펴 보고자 하는 상급자
> 자세한 Prerequisites은 Lecture 1을 참고하시기 바랍니다.
많은 분들의 관심과 격려로 힘내고 있습니다. 감사합니다 :D
그리고 또한 많은 분들께서 오역, 오타관련 Issues, Pull requests, Email 등을
보내주시고 계십니다. 특히 오타 찾는게 정말 힘든데 이렇게 도와주시니 정말 감사할 따릅입니다 :D
현재 draft 버전은 오역, 오타, 싱크 등 문제가 많습니다.
오역, 오타, 싱크 문제는 지속적으로 업데이트하고 있으며, first revision을 작업중입니다.
first revision이 draft버전보다 많이 개선된 버전이므로 참고해주시기 바랍니다.
다시 한번 모두에게 감사드립니다 XD
Instructors
Fei-Fei Li: http://vision.stanford.edu/feifeili/
Justin Johnson: http://cs.stanford.edu/people/jcjohns/
Serena Yeung: http://ai.stanford.edu/~syyeung/
Prerequisites
Any video player with codecs which might be let you watch lectures
Recommendation
Windows : PotPlayer(kakao)
Linux : SM Player
IOS : Whatever you can :(
Usage
-
You should download lectures from youtube
- You need a video downloader like 4k video downloader (maybe support most of platforms like Windows, Linux(Ubuntu), MacOS)
- Download this Youtube Playlist with downloader
- If you take "4k video downloader", you can download whole lectures "at once" not "each", with Playlist.
-
and Enjoy videos with Subtitles
root └── eng └── Subtitles in English. └── kor └── Subtitles in Korean.
Update Note
Welcome to Pull Request
1. Update News
...
2018.05.23 - Complete Lecture 6(draft)
2018.06.14 - Complete Lecture 7(draft)
2018 06 26 - Complete Lecture 8(draft)
2018 07 27 - Complete Lecture 1(1st Revision)
2018 07 09 - Complete Lecture 9(draft)
2018 07 16 - Complete Lecture 2(1st Revision)
2018 07 30 - Complete Lecture 10(draft)
2018 08 13 - Complete Lecture 11(draft)
2018 09 24 - Complete Lecture 12(draft)
2018 10 06 - Complete Lecture 13(draft)
2018 12 31 - Complete Lecture 14(draft)
1. Milestone
Lecture 01 : Complete(draft + 1st Revision)
Lecture 02 : Complete(draft + 1st Revision)
Lecture 03 : Complete(draft)
Lecture 04 : Complete(draft)
Lecture 05 : Complete(draft)
Lecture 06 : Complete(draft)
Lecture 07 : Complete(draft)
Lecture 08 : Complete(draft)
Lecture 09 : Complete(draft)
Lecture 10 : Complete(draft)
Lecture 11 : Complete(draft)
Lecture 12 : Complete(draft)
Lecture 13 : Complete(draft)
Lecture 14 : Complete(draft)
Invited Talk 1 : not yet :(
Invited Talk 2 : not yet :(
Table of Contents (CS231n 2017)
Please see also
Status info
Status info | Symbol | Status info | Symbol |
---|---|---|---|
Draft | :pencil2: | 1st_revision | :pencil2: :scissors: |
not yet | :no_bell: | 2nd_revision | :pencil2: :scissors: :scissors: |
Event Type | Description | Videos(youtube) | Slides | Subtitles | Status |
---|---|---|---|---|---|
Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition | video | slide | english | :pencil2: :scissors: |
Lecture 2 | Image Classification | video | slide | english | :pencil2: :scissors: |
Lecture 3 | Loss Functions and Optimization | video | slide | english | :pencil2: |
Lecture 4 | Introduction to Neural Networks | video | slide | english | :pencil2: |
Lecture 5 | Convolutional Neural Networks | video | slide | english | :pencil2: |
Lecture 6 | Training Neural Networks I | video | slide | english | :pencil2: |
Lecture 7 | Training Neural Networks II | video | slide | english | :pencil2: |
Lecture 8 | Deep Learning Software | video | slide | english | :pencil2: |
Lecture 9 | CNN Architectures | video | slide | english | :pencil2: |
Lecture 10 | Recurrent Neural Networks | video | slide | english | :pencil2: |
Lecture 11 | Detection and Segmentation | video | slide | english | :pencil2: |
Lecture 12 | Visualizing and Understanding | video | slide | english | :pencil2: |
Lecture 13 | Generative Models | video | slide | english | :pencil2: |
Lecture 14 | Deep Reinforcement Learning | video | slide | english | :pencil2: |
Guest Lecture | Invited Talk: Song Han Efficient Methods and Hardware for Deep Learning |
video | slide | english [korean] |
:no_bell: |
Guest Lecture | Invited Talk: Ian Goodfellow Adversarial Examples and Adversarial Training |
video | slide | english [korean] |
:no_bell: |
Screenshot
Contributors
- Jaewon Lee (Image Processing & Computer Vision Lab, KNU)
- Azure (Image Processing & Computer Vision Lab, KNU)
LICENSE
MIT