Natural Language Processing

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来源：www.coursera.org

10个序列

等级：入门

语言：英语

640分

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80小时总数

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Have you ever wondered how to build a system that automatically translates between languages? Or a system that can understand natural language instructions from a human? This class will cover the fundamentals of mathematical and computational models of language, and the application of these models to key problems in natural language processing.

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课程大纲

Topics covered include:

1. Language modeling.
2. Hidden Markov models, and tagging problems.
3. Probabilistic context-free grammars, and the parsing problem.
4. Statistical approaches to machine translation.
5. Log-linear models, and their application to NLP problems.
6. Unsupervised and semi-supervised learning in NLP.

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Michael Collins

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For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.