Statistical Natural Language Processing (MA030131)


Course Memo

This course gives introductory insights into methods that are used in natural language processing systems. This is an introductory NLP course dedicated to classic algorithms and models for NLP yet with the coverage of some more recent neural models. The course is largely based on the Jurafsky&Martin textbook, but also features lectures on graph-based models for NLP and data annotation for NLP. If you would like to get a course on purely "modern" neural NLP methods similar to Stanford's CS224n, then you shall enroll in the "Neural Natural Language Processing" course at Skoltech. Thus, given a very broad scope of NLP, we decided to split the sheer volume of material into these two complementary 3 credit courses. Goals of this course: - understand methods for language processing in detail - the ability to plan technology requirements for a language tech project - analyze and evaluate the use of NLP in applications - see the beauty of language technology, be ready to write your thesis in language tech.