Open Courses

15 Machine Learning Online Courses and Tutorials

Here we include 15 machine learning courses and tutorials by leading researchers in the field. Nine of the 15 courses include video lectures. Most of the courses are free and self-paced without the need of registration. The topics covered by these courses include decision trees, Naive Bayes, logistic regression, neural networks and deep learning, estimation, Bayesian learning, support vector machines and kernel methods, clustering, unsupervised learning, boosting, reinforcement learning, and learning theory. If you need to review background for machine learning, professor Geoff Gordon at Carnegie Mellon University has made a great video lecture series Math Background for Machine Learning. For advanced deep learning courses, see 15 deep learning open courses and tutorials for both theoritcal and applications of deep learning.

Introduction to Neural Networks and Machine Learning

Geoffrey E. Hinton. University of Toronto. 2014

This course includes video lectures

Machine Learning

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

Machine Learning and Pattern Recognition

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

Learning from Data

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

This course includes video lectures

Machine Learning

Kilian Weinberger. Cornell. 2017

Mobile friendly lecture notes

Machine Learning

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

This course includes video lectures

Neural Networks for Machine Learning

Geoffrey Hinton. University of Toronto via Coursera. 2017

This course includes video lectures. This is the newer version of his 2014 course

Machine Learning and Adaptive Intelligence

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

This course includes video lectures

Information Theory, Pattern Recognition, and Neural Networks

David J. C. MacKay. University of Cambridge via Videolectures.

This course includes video lectures

Machine Learning

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

This course includes video lectures

Machine Learning

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

This course includes video lectures

Introduction to Machine Learning

Sargur Srihari. University at Buffalo. 2017

Machine Learning - Nano Degree

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

This course includes video lectures

Tutorial: Machine Learning

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



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