An introduction to foundational ideas in computational linguistics, such as: n-gram language models; noisy channel models; supervised and unsupervised learning; and distributional semantics. Focus on developing an understanding of the intuitions behind the ideas, including relevant algorithms and math, and implementing this understanding in hands-on programming applications. May be taken for graduate credit using the LING 297 course code.

Prerequisites: Linguistics 102 or Computer Science 8 or equivalent experience.

4

Units

Optional

Grading

1, 2, 3

Passtime

None

Level Limit

Letters and science

College
TODD S J
No info found

Lecture

NH 1105
M W
11:00 AM - 12:15 PM
30 / 60

Sections

PHELP1448
T
09:00 AM - 09:50 AM
10 / 30
ILP 3101
R
15:00 PM - 15:50 PM
20 / 30
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