Natural Language Processing

582602
5
Algoritmit ja koneoppiminen
Syventävät opinnot
The course will cover state-of-the-art approaches to problems in NLP. We will consider only analyzing written language (not speech). Levels of linguistic analysis we will address: morphology, syntax, semantics, discourse analysis. We will cover standard methods of language analysis that support NLP applications, i.e., rule-based and statistical approaches, and consider some applications in depth: language modeling, bag-of-word models, spell-checking, part-of-speech tagging, parsing. We will use techniques from machine learning: hidden Markov models (HMM) and related algorithms (Viterbi, Forward algorithm, Forward-Backward algorithm), the EM algorithm, unsupervised learning. Students are graded based on 6 compulsory assignments and 2 projects. No exam. Prerequisites: Data Structures and Models of Computation; Strong programming skills; Good knowledge of design and analysis of algorithms; Although the course will introduce the needed mathematical tools, a good level of mathematical maturity is presumed: linear algebra, probability theory, etc.; An understanding of linguistic concepts is required: grammar, word and sentence structure, parts of speech, etc.
Vuosi Lukukausi Päivämäärä Periodi Kieli Vastuuhenkilö
2014 syksy 02.09-16.10. 1-1 Englanti Roman Yangarber

Luennot

Aika Huone Luennoija Päivämäärä
Ti 10-12 C222 Roman Yangarber 02.09.2014-16.10.2014
To 10-12 B222 Roman Yangarber 02.09.2014-16.10.2014