CS 295: Statistical NLP Winter 2018

From: http://www.zdnet.com/pictures/six-things-you-may-not-know-about-the-cloud/4/
Instructor Sameer Singh
Lectures SH 128 TuTh 2:00-3:20
Office Hours DBH 4204 Signup here
Course Code 35000
Other Links Piazza, Canvas

A computer’s ability to read, learn, and understand language is becoming of utmost importance with access to enormous amounts of digitized text (that we can’t possibly read), with personal communication increasingly becoming digital (that we can’t possibly remember), and with autonomous agents becoming bigger parts of our everyday lives (with whom we need to talk to). This course will introduce the historical and recent approaches to natural language processing, in particular focusing on the computational tasks and the machine learning techniques involved in NLP that have achieved incredible successes.

Tentatively, the course will cover the following topics:

At minimum:
  • An introductory machine learning course (CS 178, CS 273A, or equivalent), although an advanced course like CS 274B is a plus.
  • An introductory artificial intelligence course (CS 171 or equivalent).
  • Programming assignments will require a working familiarity with Python, along with familiarity with data structures and algorithms.
Contact me if you are concerned about your background for the course.
Grading Policy
  • 4 programming assignments: 40%
  • 3 paper summaries: 15%
  • Final project: 30%
  • Participation (quizzes, Piazza, course evaluations): 15%
We will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates and myself. Rather than emailing questions to me, I encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com.

Find our class page at: https://piazza.com/uci/winter2018/nlp/home

Academic Honesty
Academic honesty is a requirement for passing this class. Any student who compromises the academic integrity of this course is subject to a failing grade. The work you submit must be your own. Academic dishonesty includes, but is not limited to copying answers from another student, allowing another student to copy your answers, communicating exam answers to other students during an exam, attempting to use notes or other aids during an exam, or tampering with an exam after it has been corrected and then returning it for more credit. If you do so, you will be in violation of the UCI Policies on Academic Honesty (see link). It is your responsibility to read and understand these policies. Note that any instance of academic dishonesty will be reported to the Academic Integrity Administrative Office for disciplinary action and may be cause for a failing grade in the course.