• 11.14.2017: Midterm solution is here
  • 11.01.2017: The midterm will be on 11/9 in class. It will cover the lectures until 10/19.
  • 10.26.2017: Please see the instructions for project proposal here
  • 10.25.2017: Here is a Practice quiz for the midterm exam. Note that the previous quiz covers slighlty different materials from this midterm.
  • 10.10.2017: Please sign up your presentaiton group here
  • 10.06.2017: Please enroll in Piazza.
  • 09.23.2017: Welcome to CS 269: Seminar: Machine Learning in Natural Language Processing

Course Information:


  • Time: Tue/Thu 2:00pm – 3:50pm.
  • Location: Franz Hall 2258A


  • Instructor: Kai-Wei Chang, Email to:
    • Office hour: 4:00pm – 5:00pm, Tue
    • Office location: BH 3732J
  • TA: Md Rizwan Parvez, Email to:
    • Office hour: 11:00am – 1:00pm, Monday
    • Office location: BH 2432

Course Description

Natural language processing (NLP) enables computers to use and understand human languages. Recently, NLP techniques have been widely used in many applications including machine translation, question answering, and extracting information from text. In this course, we will cover the fundamental elements and recent research trends in NLP. Tentative topics include syntactic analysis, semantic analysis, and NLP applications as well as the underlying machine learning methods that widely used in modeling NLP systems. The activities of the course include lectures, paper presentations, quizzes, a critical review report, and a final project.

Tentative topics include:

  • Machine learning background: linear classification models, basic structured prediction models
  • Syntactic analysis: part-of-speech tagging, chunking, dependency parsing, constituency parsing.
  • Semantics: brown clusters, vector-space semantics, semantic role labeling.
  • NLP Applications: name entity recognition, machine translation, information extraction.


    Students are expected to have taken a class in linear algebra and in probability and statistics and a basic class in theory of computation and algorithms. Programming experience is necessary for the final project.


Recent papers published in related conferences