Real-World, Man-Machine Algorithms

Behind the scenes, the same call automatically and invisibly decides whether a machine learning classifier is reliable enough to classify the example on its own, or whether human intervention is needed. Models get built automatically, they're continually retrained, and the caller never has to worry whether more data is needed. In the rest of this article, we'll go into more detail on the problems we described above--problems that are common to all efforts to deploy machine learning to solve real-world problems. In order to train any spam classifier, you'll first need a training set of "spam" and "not spam" labels.