【荐课】2018年不容错过的15+1门免费机器学习课程（最早明天开始注册）

原标题：【荐课】2018年不容错过的15+1门免费机器学习课程（最早明天开始注册）

Hinton、吴恩达、LeCun等领域内的大师讲授，有理论、有实践，还有面向机器学习工程师的课程，配套资料丰富，向想学习并且进一步提高机器学习水平的你，诚心推荐。

Ruslan Salakhutdinov，CMU，苹果AI研究总监

Yaser S. Abu-Mostafa，加州理工，2012年

Kilian Weinberger，康奈尔大学，2017年

Roger Grosse，多伦多大学，2017年

David MacKay，剑桥大学

Tom Mitchell & Maria-Florina Balcan，CMU，2015年

佐治亚理工，2017年

Sargur Srihari，布法罗大学，2017年

Udacity 纳米学位

机器学习的数学背景

1、Introduction to Neural Networks and Machine Learning

Geoffrey E. Hinton. University of Toronto. 2014

2、Neural Networks for Machine Learning

Geoffrey Hinton.University of Toronto via Coursera.2017

3、Machine Learning

Ruslan Salakhutdinov. Carnegie Mellon University, Director of AI Research at Apple. This course was taught at University of Toronto. 2015

4、Machine Learning and Pattern Recognition

Yann LeCun. New York University, Director of AI Research at Facebook 2010

5、Learning from Data

Yaser S. Abu-Mostafa. California Institute of Technology. 2012

6、Machine Learning

Kilian Weinberger. Cornell. 2017

7、Machine Learning

Andrew Ng. Stanford University via Coursera. Founder of Coursera. 2017

8、Machine Learning and Adaptive Intelligence

Neil Lawrence. University of Sheffield, Director of Machine Learning at Amazon. 2015

9、Intro to Neural Networks and Machine Learning

Roger Grosse. University of Toronto. 2017

10、Information Theory, Pattern Recognition, and Neural Networks

David MacKay. University of Cambridge via Videolectures.

11、Machine Learning

Tom Mitchell and Maria-Florina Balcan. Carnegie Mellon University. 2015

12、Machine Learning

Michael Littman, Charles Isbell, and Pushkar Kolhe. Georgia Institute of Technology via Udacity. 2017

13、Introduction to Machine Learning

Sargur Srihari. University at Buffalo. 2017

14、Machine Learning - Nano Degree

Arpan Chakraborty, David Joyner, Luis Serrano, Sebastian Thrun, Vincent Vanhoucke, and Katie Malone. Udacity. 2017

15、Tutorial: Machine Learning

Andrew Moore. Dean of School of Computer Science at Carnegie Mellon University.