本文推荐15个机器学习课程和行业领先大牛的教程。其中大多数课程都是免费的,无需注册即可自学。内容包括决策树、朴素贝叶斯、逻辑回归、神经网络和深度学习、估计、贝叶斯学习、支持向量机和核方法(kernel)、聚类、无监督学习、提升算法(boosting)、强化学习和学习理论(learning theory)。
如果你需要回顾一下机器学习的背景知识,卡内基梅隆大学(Carnegie Mellon University)的Geoff Gordon教授的机器学习系列课程非常值得学习:机器学习的数学背景(Math Background for Machine Learning)
https://www.youtube.com/playlist?list=PL7y-1rk2cCsAqRtWoZ95z-GMcecVG5mzA 。
神经网络与机器学习简介(Introduction to Neural Networks and Machine Learning)
Geoffrey E. Hinton. University of Toronto. 2014
https://sky2learn.com/preview-wjP3pHdRJvFJK-nXdR1_kg
机器学习(Machine Learning)
Ruslan Salakhutdinov. Carnegie Mellon University, Director of AI Research at Apple. This course was taught at University of Toronto. 2015
https://sky2learn.com/preview-dFtevIcJ3Af6CputGezgDA
机器学习和模式识别(Machine Learning and Pattern Recognition)
Yann LeCun. New York University, Director of AI Research at Facebook 2010
https://sky2learn.com/preview-QiHThsEgAVEy4-odxkX1Ng
从数据中学习(Learning from Data)
Yaser S. Abu-Mostafa. California Institute of Technology. 2012
https://sky2learn.com/preview-4sLonxjTQNRtKIrJ6xCkAg
机器学习(Machine Learning)
Kilian Weinberger. Cornell. 2017
Mobile friendly lecture notes
https://sky2learn.com/preview-Pq1N3D-lXlencKqqPYxANQ
机器学习(Machine Learning)
Andrew Ng. Stanford University via Coursera. Founder of Coursera. 2017
starts on 2017/12/25
https://sky2learn.com/preview-7W3n96KtqMr-3LLpsFuM2Q/
面向机器学习的神经网络(Neural Networks for Machine Learning)
Geoffrey Hinton. University of Toronto via Coursera. 2017
The newer version of his 2014 course, starts on 2017/12/25
https://sky2learn.com/preview-E9cbKYvP0WjpeNEGBkiUOA/
机器学习和自适应智能(Machine Learning and Adaptive Intelligence)
Neil Lawrence. University of Sheffield, Director of Machine Learning at Amazon. 2015
https://sky2learn.com/preview-Qo6n50aBrr1_Ku_Yd8XkJw/
神经网络和机器学习的介绍(Intro to Neural Networks and Machine Learning)
Roger Grosse. University of Toronto. 2017
https://sky2learn.com/preview-6dHXgYG3W_OCmPgPy3akGg
信息论,模式识别和神经网络(Information Theory, Pattern Recognition, and Neural Networks)
David MacKay. University of Cambridge via Videolectures.
https://sky2learn.com/preview-waGKXtKmz8A9MZZjkbnXMw/
机器学习(Machine Learning)
Tom Mitchell and Maria-Florina Balcan. Carnegie Mellon University. 2015
https://sky2learn.com/preview-F6w_2HD9j2tvUNfxE1RrNA/
机器学习(Machine Learning)
Michael Littman, Charles Isbell, and Pushkar Kolhe. Georgia Institute of Technology via Udacity. 2017
https://sky2learn.com/preview-AtFhs-yWq9fPxaDgSe_YcA
机器学习简介(Introduction to Machine Learning)
Sargur Srihari. University at Buffalo. 2017
https://sky2learn.com/preview-_wrGYyY4Rt0ExRCGN7Oytw/
机器学习——纳米级介绍(Machine Learning - Nano Degree)
Arpan Chakraborty, David Joyner, Luis Serrano, Sebastian Thrun, Vincent Vanhoucke, and Katie Malone. Udacity. 2017
https://sky2learn.com/preview-XjNZGyJsqwXORImXYdsURQ/
机器学习教程(Tutorial: Machine Learning)
Andrew Moore. Dean of School of Computer Science at Carnegie Mellon University.
https://sky2learn.com/preview-XjNZGyJsqwXORImXYdsURQ/
参考链接:
http://bigdata.evget.com/post/2183.html
-END-
专 · 知
人工智能领域主题知识资料查看获取:【专知荟萃】人工智能领域25个主题知识资料全集(入门/进阶/论文/综述/视频/专家等)
同时欢迎各位用户进行专知投稿,详情请点击:
【诚邀】专知诚挚邀请各位专业者加入AI创作者计划!了解使用专知!
请PC登录www.zhuanzhi.ai或者点击阅读原文,注册登录专知,获取更多AI知识资料!
请扫一扫如下二维码关注我们的公众号,获取人工智能的专业知识!
请加专知小助手微信(Rancho_Fang),加入专知主题人工智能群交流!
点击“阅读原文”,使用专知!