Machine Learning, NLP, Perceptron, Tagging, From The Archives.
skip-gram embeddings ruled the land) the predominant approach for sequence tagging was to hand engineer a large number of features, and use them to train some kind of maximum-entropy model (e.g. logistic regression)[1] or conditional random field (CRF)[2]. In this paper, Michael Collins introduces