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1 - 3 of 3 results for: CS124

CS 124: From Languages to Information (LINGUIST 180, LINGUIST 280)

Automated processing of less structured information: human language text and speech, web pages, social networks, genome sequences, with goal of automatically extracting meaning and structure. Methods include: string algorithms, automata and transducers, hidden Markov models, graph algorithms, XML processing. Applications such as information retrieval, text classification, social network models, machine translation, genomic sequence alignment, word meaning extraction, and speech recognition. Prerequisite: CS103, CS107, CS109.
Terms: Win | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Jurafsky, D. (PI)

CS 224N: Natural Language Processing (LINGUIST 284)

Methods for processing human language information and the underlying computational properties of natural languages. Syntactic and semantic processing from linguistic and algorithmic perspectives. Focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, translation, and interpretation; and representative systems. Prerequisites: CS124 or CS121/221.
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Manning, C. (PI)

LINGUIST 284: Natural Language Processing (CS 224N)

Methods for processing human language information and the underlying computational properties of natural languages. Syntactic and semantic processing from linguistic and algorithmic perspectives. Focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, translation, and interpretation; and representative systems. Prerequisites: CS124 or CS121/221.
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Manning, C. (PI)
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