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Course Details

Spring 2017-2018
COS 495   na, npdf

Special Topics in Computer Science - Natural Language Processing

Sida Wang

Methods and algorithms for natural language understanding with an emphasis on machine learning and deep learning approaches. Study topics such as language modeling, lexical semantics, distributed representations of meaning, syntactic and semantic parsing as a structured prediction problem, recurrent neural networks and related models such as long-short-term-memory, sequence-to-sequence learning and attention. Possible applications include grammar correction, sentiment analysis, machine translation, question answering, and natural language interfaces.

Sample reading list:
Daniel Jurafsky and James H. Martin, Speech and Language Processing
See instructor for complete list

Reading/Writing assignments:
Student is expected to read 10-20 pages per week. Assignments with programming every 2 weeks.

Requirements/Grading:
Final Exam - 20%
Design Project - 20%
Programming Assignments - 60%

Other Requirements:
Not Open to Freshmen.

Prerequisites and Restrictions:
Prerequisites: multivariate calculus (MAT 201), linear algebra (MAT 202), programming python will be most used. Familiarity with probability, statistics, and machine learning..

Website:  http://www.cs.princeton.edu/courses/archive/spring18/cos495/

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
40266 L01 1:30 pm - 2:50 pm T Th        Enrolled:50 Limit:50 Closed
40267 P01 10:00 am - 10:50 am M        Enrolled:25 Limit:25 Closed
40268 P02 1:30 pm - 2:20 pm W        Enrolled:25 Limit:25 Closed