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COURSE
INFORMATION
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Instructor and TAs
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| When/Where |
420-041 Tuesday 9:30-10:45am
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| Portal |
The portal for the online part of the class has now been set up as
https://stanford.campus-class.org/lang2info/class. |
| Discussion |
The class forum for all technical questions and bug reports is here:
https://stanford.campus-class.org/lang2info/forum/list?forum_id=2
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| Email |
Mail non-technical questions only to cs124-win1112-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-win1112-staff@lists.stanford.edu to make an appointment.
This mailing address is for Stanford CS124 students only, not for students enrolled in the public Natural Language Processing class. All inquiries should be sent from a stanford.edu email address, so we know that you're a Stanford student.
We use the mailing list generated by Axess to convey messages to the class. We will assume that all students read these messages.
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| Textbooks |
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Required: Jurafsky and Martin. 2009. Speech and Language Processing (2nd Edition). Pearson
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Recommended: Manning, Raghavan, and Schütze. 2008.
Introduction to Information Retrieval. Cambridge
University Press.
Readings from MR+S are required, but it's ok to do readings online here or
here (the published book, for Stanford users).
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| 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.
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| Prerequisites |
CS 103, CS 107, CS 109.
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| 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 quizzes are not counted toward the final grade.
Lectures for each week must be watched by noon Monday of the following week
- Automated Review Quizzes:
After watching a week's video lectures, we will ask you to answer a 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 mornings will be used for
problem-solving, reviews, discussions, guest speakers from industry, and presentation of state-of-the-art research.
The in-class sessions are optional, but strongly recommended.
You can get extra credit for class participation by answering questions on the class forum.
- Homeworks: 7 homeworks (6 programming (in Java or Python, your choice) and one problem set). Homework is due at 10:00am on the Friday it is due.
(Unless otherwise stated on the homework; we have given you extra time on homework 1, which is due at 5:00pm)
- 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: I will expect you to do a significant amount of textbook reading in this course.
- Final Exam: Thursday Mar 22, 12:15pm-3:15pm
- Final grade:
60% homeworks, 5% exercises and videos, 35% final exam, extra credit for class participation
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