A collection of the industry’s most popular online machine learning courses

A collection of the industry’s most popular online machine learning courses

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• The cloud community
• Deep learning
• The neural network

Abstract: Machine learning is the most popular online course for advanced technology.

Here, we’ve put together 15 machine learning courses. Most of the courses are free and you don’t need to register to study. These courses include decision trees, Naive Bayes, logistic regression, neural networks and deep learning, Bayesian learning, support vector machines and kernel methods, clustering, unsupervised learning, reinforcement learning, and learning theory.

If you need to review the background on machine learning, Professor Jeff Gordon of Carnegie Mellon University has done a great video lecture series on the mathematical background for machine learning. You can learn that first, and then go on to deeper machine learning.

1. Introduction to Neural Networks and Machine Learning: Jeffrey E. Hinton, University of Toronto.2014.

2. Machine learning: Ruslan Salakhutdinov, Director of AI research at Apple, Carnegie Mellon University. This course is taught at the University of Toronto.2015.

3. Machine learning and Pattern Recognition: Yann LeCun, director of the Institute for Human Development at New York University, now at Facebook.2010.

4. Learning from data: Yaser S. Abu-Mostafa, California Institute of Technology.2012

5. Machine learning: Killian Weinberg, Cornell University.2017

6. Machine Learning: Andrew Ng, Coursera, Stanford University, starting December 25, 2017

7. Neural Networks for Machine Learning: Jeffrey Hinton, University of Toronto, Coursera. The new version of his 2014 course starts on December 25, 2017.

8. Machine learning and adaptive Intelligence: Neil Lawrence, Director of Machine Learning at Amazon, University of Sheffield, 2015.

9. Introduction to Neural networks and machine learning: Roger Gross, University of Toronto.2017.

10. Information Theory, Pattern Recognition and Neural Networks: David Mackay, Cambridge University.

11. Machine learning: Tom Mitchell and Maria Florina Balkan, Carnegie Mellon University. In 2015.

12. Machine learning: Michael Littman, Charles Isbell, and Pushkar Kolhe, Georgia Institute of Technology through Udacity.2017.

13. Introduction to machine Learning: Sargur Srihari, University of Buffalo, 2017.

14. Machine Learning – Nano Degree: Arpan Chakraborty, David Joyner, Luis Serrano, Sebastian Thrun, Vincent Vanhoucke, and Katie Malone, Udacity.2017.

15. Machine learning: Andrew Moore, dean of the School of Computing at Carnegie Mellon University.

PS: If your English is not very strong, welcome to watch the online course of machine Learning produced by Ali Yun University.

This article is recommended by Beijing Post @ Love coco – Love life teacher, translated by Ali Yunqi Community organization.

15 Machine Learning Online Courses and Tutorials

By Sky https://sky2learn.com/

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