How do you learn machine learning? A good way to start is to take an online course. These courses started appearing towards the end of 2011, first from Stanford University, now from Coursera, Udacity, edX and other institutions. There are very many of them, including a few about machine learning. Here’s a list:
Introduction to Artificial Intelligence by Sebastian Thrun and Peter Norvig. That was the first online class, and it contains two units on machine learning (units five and six). Both instructors work at Google. Sebastian Thrun is best known for building a self-driving car and Peter Norvig is a leading authority on AI, so they know what they are talking about. After the success of the class Sebastian Thrun quit Stanford to found Udacity, his online learning startup.
Machine Learning by Andrew Ng. Again, one of the first classes, by Stanford professor who started Coursera, the best known online learning provider today. Andrew Ng is a world class authority on machine learning, and this course is a good place to start. It features well chosen topics (notably missing are trees and ensembles) and programming assignments (Matlab/Octave).
Neural Networks for Machine Learning by Geoffrey Hinton. Prof. Hinton is THE man when it comes to neural networks, so this is a must-take if you are interested in them. Even though this is an advanced course, you can still watch the parts about applications for inspiration even if you are not up to speed on the subject. Matlab/Octave.
Learning From Data by Yaser Abu-Mostafa. This course has a strong emphasis on theory of learning. Fortunately the professor’s delivery is very well polished and relatively easy to comprehend. It also differs from other courses in that it is broadcasted live, so you can watch the lecture and ask your question afterwards by means of an online chat. Some programming exercises.
Machine Learning by Pedro Domingos. Currently only a preview is available. The course has an interesting and pretty comprehensive choice of topics and the content is good, even though video quality is not quite up to par with other courses.
Big Data, Large Scale Machine Learning by John Langford (think Vowpal Wabbit) and Yann LeCun (think convolutional neural networks, specifically LeNet-5). It’s not a full-fledged online course, just videos, but maybe worth mentioning because of the topic and the instructors.
Introduction to Data Science by Bill Howe. The lecturer seems to be pretty smart and engaging at the same time, and the material pretty interesting.
Besides these classes, there are at least two about natural language processing and even more about statistics and programming. One example is Computing for Data Analysis by Roger Peng, a very good introduction to R programming language. Another, Data Analysis - very relevant for machine learning - by Jeff Leek.
A revolution in higher education is underway, so take your part. Be sure to browse Udacity courses, they are generally easier to digest than Coursera’s. This site will help you to keep tabs on all classes: www.class-central.com.