Machine Learning 관련 사이트 정리

* 정기적으로 업데이트 할 예정입니다.

[무료 동영상 강좌]

1. "모두를 위한 머신러닝과 딥러닝 강의" - 김성훈 교수님(홍콩과기대)

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

2. "Coursera Machine Learning" - Andrew Ng 교수님(Stanford University)

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

3. "(기계학습,인공지능,머신러닝)한국어 기계학습 강좌" - 문일철 교수님(KAIST)

https://www.youtube.com/channel/UC9caTTXVw19PtY07es58NDg/playlists

4. "러닝 딥러닝" - 이찬우 연구원

https://www.youtube.com/channel/UCRyIQSBvSybbaNY_JCyg_vA/playlists

5. "Udacity Deep Learning" - Google

https://www.udacity.com/course/deep-learning--ud730

[관련사이트]

1. "스탠포드 CS231n 강의 번역 프로젝트"

http://aikorea.org/cs231n/

2. "데이터 사이언스 스쿨"

https://datascienceschool.net/

[해외 대학]

1. "CS229: Machine Learning - Stanford University"

http://cs229.stanford.edu/

2. "CS 189. Introduction to Machine Learning - UC Berkeley"

http://www.eecs189.org/

3. "CS 20: Tensorflow for Deep Learning Research - Stanford University"

http://web.stanford.edu/class/cs20si/

4. "CS231n: Convolutional Neural Networks for Visual Recognition - Stanford University"

http://vision.stanford.edu/teaching/cs231n/

5. "CS221: Artificial Intelligence: Principles and Techniques - Stanford University"

https://web.stanford.edu/class/cs221/

6. "CS224n: Natural Language Processing with Deep Learning - Stanford University"

https://web.stanford.edu/class/cs224n/index.html

7. "CS188. Intro to AI - UC Berkeley"

http://ai.berkeley.edu/project_overview.html

[소스 코드]

1. "골빈해커의 3분 딥러닝" - Tensorflow Tutorials (한글 주석)

https://github.com/golbin/TensorFlow-Tutorials

2. "CS 20: TensorFlow for Deep Learning Research" - Stanford Tensorflow Tutorials

https://github.com/chiphuyen/stanford-tensorflow-tutorials

[데이터]

1. "kaggle" - 10000개 이상의 다양한 데이터셋

https://www.kaggle.com/datasets

2. "Deep Learning Datasets" - 텍스트, 음성, 사진 등 딥러닝 알고리즘에서 사용 가능한 데이터셋

http://deeplearning.net/datasets/

3. "IMDB-WIKI – 500k+ face images with age and gender labels" - 얼굴 사진 데이터셋

https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/

4. "UCI Machine Learning Repository: Data Sets" - 연습용으로 사용할 수 있는 다양한 데이터셋

https://archive.ics.uci.edu/ml/datasets.html