Statistical Natural Language Processing
Download as PDF
Overview
Description
This course provides a survey of the challenges, concepts and methodologies employed in Natural Language Processing (NLP). The subject brings together the modeling of the underlying structure of human language with the flexibility and power of neural networks and other algorithmic approaches. The course covers modeling the parts of speech, disambiguation, text similarity, maximum entropy methods, neural networks, and computational semantics.
Career
Graduate
Credits
Value
1.5
Max
1.5
Min
1.5
Course Count
1
Number Of Credits
1.5
Number Of Repeats
1
Repeatable
No
Contact Use
Yes
Generate Attendance
No
Left Use
Yes
Present Use
Yes
Reason Use
Yes
Tardy Use
Yes
Template Override
No
Time Use
Yes
Attendance Type
Class Meeting
Auto Create
No
Code
LEC
Instructor Contact Hours
1.5
Default Section Size
30
Final Exam Type
Yes
Include in Dynamic Date Calc
No
Instruction Mode
In Person
LMS File Type
Blackboard CourseInfo 4
Name
Lecture
OEE Workload Hours
0
Optional Component
No
Preferred Room Features
Academic Scheduling
Workload Hours
1.5