DSS July 17: TOM OSBORN "Active Learning"

Active learning is a branch of semi-supervised machine learning for domains where data is expensive and where precise understanding is critical. Traditionally, active learning builds a model of a domain with a trade-off between exploration and exploitation probing of a domain to generate labelled data usefully. Earlier applications of active learning included intelligent tutoring and robotic search of a novel environment. More recent examples include algorithmic trading in online auctions and markets, recommender systems, and fast optimal classifiers.

Видео DSS July 17: TOM OSBORN "Active Learning" канала DataScienceSydney