Bayesian Analysis In Natural Language Processing

Covers the methods and algorithms that are needed to fluently read Bayesian learning papers in natural language processing (NLP) and to do research in the area. The authors explore inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modelling.