News & Resources2017. 7. 11. 14:39


[머신러닝 입문 강좌]

Andrew Ng's ML class 

https://class.coursera.org/ml-003/lecture

ML class wiki : https://share.coursera.org/wiki/index.php/ML:Main

ML1 class wiki : https://share.coursera.org/wiki/index.php/ML1:Main

note : http://www.holehouse.org/mlclass/




[모두를 위한 머신러닝(한글)]

김성훈 교수님 class

http://hunkim.github.io/ml/




[머신러닝 입문 온라인북]

Bengio textbook

http://www.deeplearningbook.org/

https://www.youtube.com/watch?v=JuimBuvEWBg




[텐서플로우]

Tensorflow

https://www.tensorflow.org

https://github.com/aymericdamien/TensorFlow-Examples

https://wookayin.github.io/TensorFlowKR-2017-talk-bestpractice/ko/#1




[이미지 처리를 위한 딥러닝 강좌]

CS231n: Convolutional Neural Networks for Visual Recognition

http://cs231n.stanford.edu/syllabus.html

http://cs23ln.github.io/

https://www.youtube.com/playlist?list=PLlJy-eBtNFt6EuMxFYRiNRS07MCWN5UIA

https://github.com/aikorea/cs231n

http://aikorea.org/cs231n/




[언어 학습을 위한 딥러닝 강좌]

CS224d: Deep Learning for NLP 2016

http://cs224d.stanford.edu/reports_2016.html

http://cs224d.stanford.edu/syllabus

https://www.youtube.com/playlist?list=PLCJlDcMjVoEdtem5GaohTC1o9HTTFtK7_




[강화 학습을 위한 딥러닝 강좌]

Reinforcement Learning

http://incompleteideas.net/sutton/book/the-book.html

https://www.youtube.com/watch?v=HYTWg9QYrW8&index=2&list=PLlMkM4tgfjnLHjEoaRKLdbpSIDJhiLtZE

RL Course by David Silver

CS 294 : Deep Reinforcement Learning



[수학, 통계]

mathematical monk

https://www.youtube.com/user/mathematicalmonk

Essence of linear algebra

https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

MIT Statistical Learning Theory

https://www.notion.so/Statistical-Learning-Theory-50ce9b93eae742f1a54fff2066e67ef8






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