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CS224N

Natural Language Processing with Deep Learning

Computer Science ENGR - School of Engineering

Course Description

Methods for processing human language information and the underlying computational properties of natural languages. Focus on deep learning approaches: understanding, implementing, training, debugging, visualizing, and extending neural network models for a variety of language understanding tasks. Exploration of natural language tasks ranging from simple word level and syntactic processing to coreference, question answering, and machine translation. Examination of representative papers and systems and completion of a final project applying a complex neural network model to a large-scale NLP problem. Prerequisites: calculus and linear algebra; CS124, CS221, or CS229.

Cross Listed Courses

Grading Basis

ROP - Letter or Credit/No Credit

Min

3

Max

4

Course Repeatable for Degree Credit?

No

Course Component

Discussion

Enrollment Optional?

Yes

Course Component

Lecture

Enrollment Optional?

No

Does this course satisfy the University Language Requirement?

No

Courses

CS224N is a prerequisite for:

Programs

CS224N is a completion requirement for:
  • (from the following course set: )
CS224N is a prerequisite for: