We’ve launched a new course, Machine Learning 2 – Unsupervised Learning, from our Georgia Tech Masters in CS track!
Join Professor Michael Littman and Professor Charles Isbell for an in depth look at how to use unsupervised learning techniques — including randomized optimization, clustering, and feature selection and transformation — to find structure in unlabeled data.
Below, the professors introduce unsupervised learning concepts in 2 minutes (and cover muffins, breakfast burritos, and ice cream on the side):
Unsupervised learning is a machine learning approach that draws inferences from unlabeled data sets. For example, when Netflix predicts what movies you’ll enjoy, and when Amazon recommends products you might want, that’s unsupervised learning at work!
In this course, you’ll put unsupervised learning to work by building your own recommendation engine, using clustering algorithms, to predict movie recommendations for thousands of users.
Happy (Machine) learning!
