학습에 참고하면 좋을 자료 Link 2 (ML)

김성훈 교수님 강의

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

https://www.youtube.com/watch?v=BS6O0zOGX4E&list=PLlMkM4tgfjnLSOjrEJN31gZATbcj_MpUm

https://www.youtube.com/watch?v=dZ4vw6v3LcA&list=PLlMkM4tgfjnKsCWav-Z2F-MMFRx-2gMGG

ratsgo님의 textmining blog

https://ratsgo.github.io/blog/categories/

CS231n Convolutional Neural Networks for Visual Recognition

http://cs231n.stanford.edu/

http://aikorea.org/cs231n/

Machine Learning 공부 step 정리

https://m.facebook.com/groups/255834461424286?view=permalink&id=490430184631378

Coursera 강의 (Andrew Ng 교수님)

https://www.coursera.org/learn/machine-learning

블로그 강의

https://tensorflow.blog/2016/04/28/first-contact-with-tensorflow/

https://m.blog.naver.com/laonple/220463627091

참고

http://t-robotics.blogspot.kr/2015/05/deep-learning.html

Deep Learning Framework 비교

https://deeplearning4j.org/kr/compare-dl4j-torch7-pylearn

deeplearning4j setting

https://deeplearning4j.org/gettingstarted

https://github.com/deeplearning4j/dl4j-examples

Mathematical Fundamentals for Data Science

http://www.kmooc.kr/courses/course-v1:KoreaUnivK+ku_eng_002+2017_A21/about