예비 지식
¶
확률과 통계
선형대수학
분류(Classification)
¶
Naive Bayesian Classifier
(http://wiki.zeropage.org/wiki.php/Naive%20Bayesian%20Classifier)
Artificial Neural Network
강화학습(Reinforce Learning)
¶
강의
UCL Course on RL
(http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html)
Youtube
(https://www.youtube.com/watch?v=2pWv7GOvuf0)
책
Reinforcement Learning: An Introduction
(http://incompleteideas.net/sutton/book/bookdraft2017june19.pdf)
Fundamental of Reinforcement Learning
(https://dnddnjs.gitbooks.io/rl/content)
Slide
Deep RL Tutorial - David Silver
(http://icml.cc/2016/tutorials/deep_rl_tutorial.pdf)
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
(https://www.slideshare.net/carpedm20/ss-63116251)
Articles
Simple Reinforcement Learning with Tensorflow 한국어 번역
(http://ishuca.tistory.com/391)
Resource
OpenAI Gym
(https://gym.openai.com)
: 실습 가능한 환경을 제공
Code
tensorflow tutorial
(https://github.com/golbin/TensorFlow-Tutorials/tree/master/10%20-%20DQN)
링크들
¶
http://wiki.zeropage.org/wiki.php/MachineLearning스터디
http://www.reddit.com/r/MachineLearning/comments/20i0vi/meta_collection_of_links_for_beginners_faq
http://peekaboo-vision.blogspot.kr/2013/01/machine-learning-cheat-sheet-for-scikit.html
Deep Learning GPU Training System
(https://github.com/NVIDIA/DIGITS)
Links
¶
https://www.coursera.org/course/neuralnets
Retrieved from http://wiki.zeropage.org/wiki.php/Machine Learning
last modified 2021-02-07 05:23:42