CS 6741
Last Updated
- Schedule of Classes - January 7, 2018 7:14PM EST
- Course Catalog - January 7, 2018 7:15PM EST
Classes
CS 6741
Course Description
Course information provided by the Courses of Study 2017-2018.
Robust language understanding has the potential to transform how we interact with computers, extract information from text and study language on large scale. However, to accurately recover the meaning of language, automated systems must learn to reason about the meaning of words and the intricate structures they combine to. This research-oriented course examines machine learning and inference methods for recovering structured representations of language meaning. Possible topics include formalisms, inference and learning for: sequence models (tagging, named-entity recognition), tree models (constituency and dependency parsing), mapping sentences to logical form representations and alignment models (machine translation).
When Offered Fall.
Permission Note Enrollment limited to: Ph.D. students.
Prerequisites/Corequisites Prerequisite: CS 2110 or equivalent programming experience, a course in machine learning (CS 4780/CS 5780, CS 6780 or equivalent).
Regular Academic Session. Combined with: CS 6741
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Credits and Grading Basis
3 Credits Graded(Letter grades only)
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Class Number & Section Details
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Meeting Pattern
- MW Bill and Melinda Gates Hll 416
Instructors
Artzi, Y
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Additional Information
Instruction Mode: Distance Learning - WWW
Class offered via distance learning, streaming from NYC.
Regular Academic Session. Combined with: CS 6741
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Credits and Grading Basis
3 Credits Graded(Letter grades only)
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Class Number & Section Details
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Meeting Pattern
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MW
Bloomberg Center 398
Cornell Tech Instructors
Artzi, Y
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MW
Bloomberg Center 398
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Additional Information
Taught in NYC. Enrollment limited to: Cornell Tech PhD students.
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