Computational Linguistics

This course is mainly for graduate students interested in Computational Linguistics / natural language processing. It mainly introduces the basic knowledge of computational linguistics, including common machine learning models, such as Bayesian classifier, decision tree, k-nearest neighbor, support vector machine SVM, logical regression, maximum entropy, hidden Markov model HMM CRFs, artificial neural networks and deep learning. At the same time, some common basic NLP tasks are also introduced, such as word segmentation, part of speech tagging, syntactic analysis, and applied NLP tasks, such as language generation, sentiment analysis, information retrieval, information extraction, etc.