CSCI 544 Applied Natural Language Processing, Fall 2016

Instructors

During our on-campus office hours, you can find us in either PHE 514 or PHE 516. In addition to the listed office hour, office hours are also by appointment. Last scheduled office hour is November 30.

Teaching Assistants

For the moment, TA office hours will be located in the SAL computer lab.

Lectures

  • Calendar
  • Section 30089D meets Mon/Wed 4-5:50PM at THH 210.
  • Section 30090D meets Mon/Wed 6-7:50PM at SAL 101.
  • Announcements

    Course summary

    This course covers both fundamental and cutting-edge topics in Natural Language Processing (NLP) and provides students with hands-on experience in NLP applications in the form of programming assignments in Python, and a group project where students have the freedom to pick the programming tools of their choice. Students are expected to have programming experience and either be familar with Python or able to quickly learn it during the first assignment.

    As we'll explore in the course, natural language is often ambiguous, and machine learning is crucial to making decisions under uncertainty. Many other tools in basic artificial intelligence (e.g., planning, knowledge representation and reasoning) also play a role in understanding and responding to natural language. However, this class is aimed at students with a general background in computer science (i.e., you don't need to take a machine learning or AI course as a prerequisite). We will cover the necessary machine learning and basic AI material in this course.

    The topics covered will be similar to last year and we anticipate discussing speech processing (language modeling, speech recognition, speech synthesis), linguistic foundations (parts of speech, syntax, speech disfluencies, semantics, dialogue, discourse), machine learning, and applications (information retrieval, information extraction, machine translation, natural language generation, dialogue systems, automated grading). There is no required text book for the course; we will use lectures to cover the material. Interested students can continue their study with other courses in USC's computational linguistics curriculum.

    Resources

    There will be a variety of resources used in this course to faciliate online discussion, distributing grades, and submitting coursework.

    Grading

    Assignments and project

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