Fighting spam is a success story of real-world machine learning. Despite the
occasional spam that does reach our inboxes, the overwhelming majority of spam —
and there is a lot of it — is positively identified. At the same time, the rarity
with which users feel the need to check their spam box for false positives
demonstrates a high precision of classification. This paper is an overview of
Google’s approach to ﬁghting email abuse with machine learning, and a discussion of
some lessons learned.