http://videolectures.net，例如輸入Zoubin
Coursera
Machine learninghttps://www.coursera.org/learn/machine-learning/ I. Introduction (Week 1): watch more than twice (能閉目聽懂，絕不再看)
II. Linear Regression with One Variable (Week 1):已看一次，內容很容易，都已理解
III. Linear Algebra Review (Week 1, Optional):絕不看，都是基本內容。20160711看兩次Lecture14 Dimensionality Reduction (Week 8)的ppt, understand completely,故視頻暫不看。
IV. Linear Regression with Multiple Variables (Week 2)和Lecture6 Logistic Regression (Week 3), Lecture7 Regularization (Week 3), Lecture8 Neural Networks Representation (Week 4), Lecture9 Neural Networks Learning (Week 5),
Lecture10 Advice for Applying Machine Learning (Week 6), Lecture11 Machine Learning System Design (Week 6), Lecture12 Support Vector Machines (Week 7), Lecture17 Large Scale Machine Learning (Week 10)已看兩次，內容很容易，都已理解，絕不再看。Lecture12在20160711看完
Lecture5 Octave Tutorial暫不看(百度百科：Octave是一種高級語言，主要設計用來進行數值計算，它是MathWorks出品的Matlab商業軟件的一個強有力的競爭產品。)
20150814將Lecture7 Regularization (Week 3)之前都已經復習兩次，并且整理出復習提綱。20150830和20150904將Lecture 10分別復習一次，絕不再看。20150904和20150912將Lecture 11和Lecture 17分別復習一次，絕不再看。
下面看Lecture13 Clustering (Week 8)
，如果課件全懂，絕不看;一定得先看以前的模式筆記,Zhihua教材, Ming Zhu教材和筆記, Jian Pei筆記。
Lecture15
Anomaly Detection，Lecture16
Recommender Systems和Lecture18即是擴充知識面，又是練英語
學法：先看無字幕版，再看有字幕版，每個最少最少看兩篇，直至閉目聽懂。 一定認真聽記筆記，很多課程都僅聽一次
Valse QQ群：張興國T-秋田大(582968216) 2017/8/31 6:39:18
吳恩達在
http://coursera.org/
上的《神經網絡和深度學習》這門課在網易云課堂上可以免費看了，還有中文字幕，感興趣的老師和同學可以去看看
應該是這個https://www.coursera.org/learn/neural-networks-deep-learning#
https://mooc.study.163.com/smartSpec/detail/1001319001.htm/?utm_source=weibo.com&utm_medium=timeline&utm_campaign=deepLearning&utm_content=wnd20170831
韓家煒教授數據挖掘龍星課程視頻
http://www.youku.com/playlist_show/id_1903290.html 韓家煒教授Pattern Discovery in Data Mining
https://www.coursera.org/course/patterndiscovery Si Liu老師在VALSE20150813-Panel推薦的Boyd的Convex Optimization課程
http://www.youtube.com/watch?v=McLq1hEq3UY;
http://stanford.edu/~boyd/cvxbook/。一個是視頻，一個是video
Mingming Chen(Nankai) recomm
end a course in Valse QQ群：牛津大學機器學習課程（PPT，講課視頻，作業，代碼等）：
https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/ Fei-Fei Li: How we're teaching computers to understand pictures
http://www.ted.com/talks/fei_fei_li_how_we_re_teaching_computers_to_understand_pictures#
[轉自靜.沙龍]斯坦福人工智能實驗室主任、計算機視覺實驗室主任Fei-Fei Li教授本月的計算機視覺TED Talk: 
http://t.cn/RAwE22v 不錯的科普教材。
美國大學線上課件大全: http://mp.weixin.qq.com/s?__biz=MzA5NzcxMzc4OQ==&mid=214275160&idx=2&sn=6e1377d47db154eb7507c6eac6f4ad26&scene=1&from=groupmessage&isappinstalled=0#rd
What we’re learning from online education: https://www.ted.com/talks/daphne_koller_what_we_re_learning_from_online_education/transcript
English teacher Tarey of Umich recommends "2016 University of Waterloo 3MT first prize winner: Gah-Jone Won". MT is short for minutes thesis. If you search "Gah-Jone Won" on youtube, you will find it.很好的科普
徐亦達老師機器學習視頻網站
http://www.valser.org/thread-725-1-1.html http://www-staff.it.uts.edu.au/~ydxu/statistics.htm Valse qq群有人說：
徐老師 講的很仔細
徐亦達老師20180407在微信群發:
大家好，最近把我的機器學習課程講義,代碼，視頻鏈接都移植到了 github 上啦 https://github.com/roboticcam/machine-learning-notes/blob/master/README.md 我以后一定每過兩天就更新一下
徐亦達老師20180513在微信群發:
大家好，為了準備7月在北航上32課時300人的機器學習課，我最近一直在努力更新課件。上個星期加了一個word representation and softmax, 講了一些自然語言處理的數學問題，包括 word2vec 優化, noise contrastive estimation, negative sampling, Gumbel max trick 等。還在努力完善中
https://github.com/roboticcam/machine-learning-notes/blob/master/word_vector.pdf
謝謝大家。這也是我第一次寫NLP 課件。[Shy][Shy]我們做了一些的nlp 工業項目。我打算趁去北航的機會。花點時間整理一下
Terry Tang: https://www.youtube.com/watch?v=SK8FRKBb2FI
徐亦達T悉尼科大<xuyida@hotmail.com> 2018/5/20 8:26:58 (Valse qq群)
大家好
整整兩年半沒有發新的機器學習視頻啦。今天終于痛下決心
從此開始堅持每星期的視頻和講義的更新。優酷地址
http://i.youku.com/u/UMzIzNDgxNTg5Ng YouTube地址
https://www.youtube.com/channel/UConITmGn5PFr0hxTI2tWD4Q 講義網址
https://github.com/roboticcam/machine-learning-notes/blob/master/README.md
張志華老師：
機器學習導論 http://ocw.sjtu.edu.cn/G2S/OCW/cn/CourseDetails.htm?Id=397
統計機器學習http://ocw.sjtu.edu.cn/G2S/OCW/cn/CourseDetails.htm?Id=398
2017年02月17日郵件:
https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html