Active Learning: getting the most out of limited data

Last week I saw an excellent talk by a researcher at Fast Forward Labs that caused me to think about the instance of machine learning called ‘active learning’. Active learning refers to a number of strategies for dealing with incompletely labeled data, particularly identifying which points to manually label.

Most of the use cases people think about when they hear the term ‘machine learning’ involve so-called ‘supervised learning’, meaning that they require data that has a labelled target variable to train on. If a bank wants to build a…