The material, while not trivial, requires no formal pre-requisites except for experience with at least one programming language, and probably some comfort with linear algebra. The web site says to expect to spend approximately 10 hours per week during the 10 week curriculum. To sign up, visit the course web site at http://www.ml-class.org.
At Hyperpublic we use machine learning in a number of places while building our places dataset. The most direct application is in our classification algorithms to determine whether a particular business might be a Japanese Restaurant, Female Shoe Store, or any of the other 300+ categories that we've defined in our ontology. We can also apply ML to solving data freshness problems and cross-referencing problems.
While we have experienced data gurus with academic ML training on the team, the rest of us academically curious engineers are looking forward to participating in the Stanford course. We'll be occasionally hosting study groups at the office and pestering one another to make sure everyone hands in their homework on time. Back to school!
Doug Petkanics
Jeff Weinstein
jordancooper
Eric Tang
mkscrg
