https://mediawiki.zeropage.org/api.php?action=feedcontributions&feedformat=atom&user=222.106.97.73 2026-05-15T03:02:25Z User contributions MediaWiki 1.39.8 https://mediawiki.zeropage.org/index.php?title=Machine_Learning&diff=34576 2017-06-24T07:38:27Z

<p>222.106.97.73: </p> <hr /> <div>== 예비 지식 ==<br /> * 확률과 통계<br /> * 선형대수학<br /> <br /> == 분류(Classification) ==<br /> * [http://wiki.zeropage.org/wiki.php/Naive%20Bayesian%20Classifier Naive Bayesian Classifier]<br /> * [[Artificial Neural Network]]<br /> <br /> == 강화학습(Reinforce Learning) ==<br /> * Book<br /> ** [https://dnddnjs.gitbooks.io/rl/content Fundamental of Reinforcement Learning]<br /> * 강의<br /> ** [http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html UCL Course on RL]<br /> ** [https://www.youtube.com/watch?v=2pWv7GOvuf0 Youtube]<br /> * 책<br /> ** [http://incompleteideas.net/sutton/book/bookdraft2017june19.pdf Reinforcement Learning: An Introduction]<br /> * Slide<br /> ** [http://icml.cc/2016/tutorials/deep_rl_tutorial.pdf Deep RL Tutorial - David Silver]<br /> ** [https://www.slideshare.net/carpedm20/ss-63116251 텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016]<br /> * Articles<br /> ** [http://ishuca.tistory.com/391 Simple Reinforcement Learning with Tensorflow 한국어 번역]<br /> * Resource<br /> ** [https://gym.openai.com OpenAI Gym] : 실습 가능한 환경을 제공<br /> == 링크들 ==<br /> * http://wiki.zeropage.org/wiki.php/MachineLearning%EC%8A%A4%ED%84%B0%EB%94%94<br /> * http://www.reddit.com/r/MachineLearning/comments/20i0vi/meta_collection_of_links_for_beginners_faq<br /> * http://peekaboo-vision.blogspot.kr/2013/01/machine-learning-cheat-sheet-for-scikit.html<br /> * [https://github.com/NVIDIA/DIGITS Deep Learning GPU Training System]<br /> <br /> == Links ==<br /> * https://www.coursera.org/course/neuralnets<br /> </div>

222.106.97.73 https://mediawiki.zeropage.org/index.php?title=Machine_Learning&diff=34575 2017-06-24T07:37:49Z

<p>222.106.97.73: </p> <hr /> <div>== 예비 지식 ==<br /> * 확률과 통계<br /> * 선형대수학<br /> <br /> == 분류(Classification) ==<br /> * [http://wiki.zeropage.org/wiki.php/Naive%20Bayesian%20Classifier Naive Bayesian Classifier]<br /> * [[Artificial Neural Network]]<br /> <br /> == 강화학습(Reinforce Learning) ==<br /> * Book<br /> ** [https://dnddnjs.gitbooks.io/rl/content Fundamental of Reinforcement Learning]<br /> * 강의<br /> ** [http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html UCL Course on RL]<br /> ** [https://www.youtube.com/watch?v=2pWv7GOvuf0 Youtube]<br /> * 책<br /> ** [http://incompleteideas.net/sutton/book/bookdraft2017june19.pdf Reinforcement Learning: An Introduction]<br /> * Slide<br /> ** [http://icml.cc/2016/tutorials/deep_rl_tutorial.pdf Deep RL Tutorial - David Silver]<br /> * Articles<br /> ** [http://ishuca.tistory.com/391 Simple Reinforcement Learning with Tensorflow 한국어 번역]<br /> * Resource<br /> ** [https://gym.openai.com OpenAI Gym] : 실습 가능한 환경을 제공<br /> == 링크들 ==<br /> * http://wiki.zeropage.org/wiki.php/MachineLearning%EC%8A%A4%ED%84%B0%EB%94%94<br /> * http://www.reddit.com/r/MachineLearning/comments/20i0vi/meta_collection_of_links_for_beginners_faq<br /> * http://peekaboo-vision.blogspot.kr/2013/01/machine-learning-cheat-sheet-for-scikit.html<br /> * [https://github.com/NVIDIA/DIGITS Deep Learning GPU Training System]<br /> <br /> == Links ==<br /> * https://www.coursera.org/course/neuralnets<br /> </div>

222.106.97.73 https://mediawiki.zeropage.org/index.php?title=Machine_Learning&diff=34574 2017-06-24T07:37:03Z

<p>222.106.97.73: </p> <hr /> <div>== 예비 지식 ==<br /> * 확률과 통계<br /> * 선형대수학<br /> <br /> == 분류(Classification) ==<br /> * [http://wiki.zeropage.org/wiki.php/Naive%20Bayesian%20Classifier Naive Bayesian Classifier]<br /> * [[Artificial Neural Network]]<br /> <br /> == 강화학습(Reinforce Learning) ==<br /> * Book<br /> ** [https://dnddnjs.gitbooks.io/rl/content Fundamental of Reinforcement Learning]<br /> * 강의<br /> ** [http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html UCL Course on RL]<br /> ** [https://www.youtube.com/watch?v=2pWv7GOvuf0 Youtube]<br /> * 책<br /> ** [http://incompleteideas.net/sutton/book/bookdraft2017june19.pdf Reinforcement Learning: An Introduction]<br /> * Slide<br /> ** [http://icml.cc/2016/tutorials/deep_rl_tutorial.pdf Deep RL Tutorial - David Silver]<br /> * Articles<br /> ** [http://ishuca.tistory.com/391 Simple Reinforcement Learning with Tensorflow 한국어 번역]<br /> == 링크들 ==<br /> * http://wiki.zeropage.org/wiki.php/MachineLearning%EC%8A%A4%ED%84%B0%EB%94%94<br /> * http://www.reddit.com/r/MachineLearning/comments/20i0vi/meta_collection_of_links_for_beginners_faq<br /> * http://peekaboo-vision.blogspot.kr/2013/01/machine-learning-cheat-sheet-for-scikit.html<br /> * [https://github.com/NVIDIA/DIGITS Deep Learning GPU Training System]<br /> <br /> == Links ==<br /> * https://www.coursera.org/course/neuralnets<br /> </div>

222.106.97.73 https://mediawiki.zeropage.org/index.php?title=Machine_Learning&diff=34572 2017-06-24T06:40:24Z

<p>222.106.97.73: </p> <hr /> <div>== 예비 지식 ==<br /> * 확률과 통계<br /> * 선형대수학<br /> <br /> == 분류(Classification) ==<br /> * [http://wiki.zeropage.org/wiki.php/Naive%20Bayesian%20Classifier Naive Bayesian Classifier]<br /> * [[Artificial Neural Network]]<br /> <br /> == 강화학습(Reinforce Learning) ==<br /> <br /> == 링크들 ==<br /> * http://wiki.zeropage.org/wiki.php/MachineLearning%EC%8A%A4%ED%84%B0%EB%94%94<br /> * http://www.reddit.com/r/MachineLearning/comments/20i0vi/meta_collection_of_links_for_beginners_faq<br /> * http://peekaboo-vision.blogspot.kr/2013/01/machine-learning-cheat-sheet-for-scikit.html<br /> * [https://github.com/NVIDIA/DIGITS Deep Learning GPU Training System]<br /> <br /> == Links ==<br /> * https://www.coursera.org/course/neuralnets<br /> </div>

222.106.97.73 https://mediawiki.zeropage.org/index.php?title=%EB%A8%B8%EC%8B%A0%EB%9F%AC%EB%8B%9D%EC%8A%A4%ED%84%B0%EB%94%94/2016&diff=50210 2017-06-24T06:37:59Z

<p>222.106.97.73: </p> <hr /> <div>&amp;#91;&amp;#91;pagelist(^(머신러닝스터디/2016))&amp;#93;&amp;#93;<br /> == 스터디 목적 ==<br /> * [[서지혜]]가 coursera에서 Andrrew Ng 교수님의 머신 러닝을 근근히 듣던 차에 알파고 - 이세돌 세기의 대결이 한국에서 열린다..! 한국인들은 크아 알파고~ 인공지능 으어 뽕을 맞았고 [[서지혜]]는 물 들어온 김에 노를 저어 스터디 원을 대 모집하게 된다. 그리고...<br /> == 목표 ==<br /> == 참여자 ==<br /> * [[서지혜]]<br /> * [[이원준]]<br /> * [[김수경]] &lt;- 탈주함<br /> * [[유재범]] &lt;- 탈주함<br /> * [[강민승]] &lt;- 탈주함<br /> * [[정의정]] &lt;- 탈주한 듯<br /> * [[변형진]] &lt;- 훈수 둠<br /> == 참여 방법 ==<br /> * Slack 채널: #machine-learning 에서 참여 의사를 밝혀주시면 됩니다.<br /> == 진행 ==<br /> * 언제: 매주 토요일 오후 3시부터<br /> * 어디서: 강남역 근처 스터디룸(주로 CMAX)<br /> * 소정의 장소비(2000원~)가 발생할 수 있습니다.<br /> === 2014년 5월 3일 - 오리엔테이션 ===<br /> * [[머신러닝스터디/2016/2016_03_19]]<br /> * 2016년 3월 19일 토요일 오후 3시<br /> ----<br /> [[활동지도/2016]], [[스터디분류]]<br /> </div>

222.106.97.73