From Languages to Information

Winter 2013

Instructor and TAs
Chris Manning, manning@cs.stanford.edu
Office: Gates 158
Office Hours: TBD
Leon Lin (Head TA), Mason Chua, Thomas Dimson, Milind Ganjoo,
Kevin Nguyen, Rukmani Ravisundaram
TA Office Hours:
  • Tuesdays 2:15 to 4:00 p.m.
  • Wednesdays 7:00 to 10:00 p.m. (Group Coding Session)
  • Thursdays 6:00 to 8:00 p.m.
Locations change, and will be updated on Piazza.
When/Where Tuesday and Thursday 9:30-10:45am in 260-113
Portal The portal for the online part of the class has now been set up as https://stanford.coursera.org/cs124-001/class.
Discussion The class forum (Piazza) for all technical questions and bug reports is here: https://piazza.com/class#winter2013/cs124 (sign up)
Email Mail non-technical questions only to cs124-win1213-staff@lists.stanford.edu. We will not reply to email sent to individual staff members. If you have a matter to be discussed privately, please come to office hours, or use cs124-win1213-staff@lists.stanford.edu to make an appointment.

We prefer that most questions are posted on the Piazza Forum - responses tend to be quicker and have a wider audience.

We use the mailing list generated by Axess to convey messages to the class. We will assume that all students read these messages.

  • Required: Jurafsky and Martin. 2009. Speech and Language Processing (2nd Edition). Pearson
  • Recommended: Manning, Raghavan, and Schütze. 2008. Introduction to Information Retrieval. Cambridge University Press.
Readings from MR+S are required, but it's okay to do the readings here (the published book).
Description Extracting meaning, information, and structure from human language text, web pages, social networks, genome sequences, or any less structured information. Methods include: string algorithms, edit distance, naive Bayes and MaxEnt classifiers, language modeling, XML processing. Applications such as information retrieval, question answering, text classification, social network models, machine translation, genomic sequence alignment, word meaning extraction.
Prerequisites CS 103, CS 107, CS 109.
Required Work
  • Video Lectures : Each week, we will ask you to watch a set of video lectures (2 to 2.5 hours total). The videos will have some in-video questions embedded in them, which you should answer. You are required to watch the videos, but the embedded quizzes are not counted toward the final grade.
  • Automated Review Quizzes: After watching a week's video lectures, we will ask you to answer an open-notes, open-book review quiz (about 5 questions) on the content that you just learned. Each review quiz may be attempted several times, with a time lag of 10 minutes in between each attempt. The questions, as well as the options for each question, are randomly selected from a larger pool each time you take a quiz. We will take the highest score over all attempts for each quiz. The first two attempts will not be penalized; subsequent attempts will incur a cumulative 20% penalty (e.g., the maximum score possible is 80% on the 3rd attempt and 60% on the 4th attempt). Review Quizzes for each week are due 10:00pm Tuesday of the following week. There are no late days for review quizzes.
  • Class Participation: Since lectures are on-line, the in-class sessions Tuesday and Thursday mornings will be used for problem-solving, reviews, discussions, guest speakers from industry, and presentation of state-of-the-art research. You can get extra credit for class participation by answering questions on the class forum.
  • Homeworks: 7 programming assignments (in Java or Python, your choice). Each assignment is due at 5:00pm on the Friday it is due.
    • Homework Collaboration: You may talk to anybody you want about the assignments and bounce ideas off each other. But you must write the actual homeworks and programs yourself.
    • Late homeworks: You have 4 free late (calendar) days to use on the homeworks. Once these are exhausted, any homework turned in late will be penalized 20% per late day. Each 24 hours or part thereof that a homework is late uses up one full late day.
  • Readings: We will expect you to do a significant amount of textbook reading in this course.
  • Final Exam: Friday Mar 22, 12:15pm-3:15pm
  • Final grade: 56% homeworks, 30% final exam, 9% weekly review quizzes, 5% attendance and participation