CS 124: From Languages to Information

FAQ

• Q: Do I have to buy a textbook? A: No, we will be using online chapters
• Q: Do I have to come to lecture or will there be videos? A: You have to come (or at least somehow learn the material from) some lectures which will not be on video
• See below and especially the end of this webpage for more details on time, location, finals schedule, etc.

Online Offering

From Languages to Information has much of the material online.

What this means:

• The lectures have been video-recorded, and you can watch them at home. The weekly quizzes and programming homeworks will be automatically uploaded and graded. Lecture, quizzes, and homeworks are available on Coursera.
• The in-class sessions will be for group problem-solving activities, but also for a few lectures by me (covering the same material as the videos), a few guest speakers from industry, review sessions, and occasional presentation of state-of-the-art research.
• Attendence is optional at all the in-class sessions except 6. Nonetheless attendence is highly recommended. Previous students who did well in the class have reported that the in-class group exercises have been extremely useful.
• However, six of the in-class sessions are required. When I say required I mean that this material is not on the videos or textbooks and will be tested in the final; I will not be taking attendence. In addition to the first day of class, There are 2 guest lectures and 3 lectures by me on course content:
  1. Tuesday, January 6, 2015: Dan's Intro lecture
  2. Thursday, January 29, 2015: Guest lecture
  3. Tuesday, Feb 17, 2015: Dan lecture on extraction of social and emotional meaning
  4. Tuesday Feb 24, 2015: Guest Lecture
  5. Thursday Mar 5, 2015: Dan lecture on social networks
  6. Tuesday Mar 10, 2015: Dan lecture on extracting meaning from everyday language
  These required lectures are marked with a * and in blue on the syllabus below.

Schedule

Course Information

Logistics

Instructor

Dan Jurafsky (jurafsky@stanford.edu)
Office: Margaret Jacks 117
Office Hours: Thursdays 2-3pm

Teaching Assistants

Adam Perelman (head TA)
Tulsee Doshi
Jon Gauthier
Vikesh Khanna
Gina Pai
Peng Qi
Pararth Paresh Shah
Jagadish Venkatraman

TA Office Hours

• Wednesdays 7:00pm to 10:00pm in Huang 203 and 219
• Tuesdays 1:15pm to 3:00pm in Huang B019
• Thursdays 6:00pm to 8:00pm in Huang B019

Class Time

Tuesday and Thursday 3:15-4:30pm in 420-40

Email

If you have a question that is not confidential or personal, post it on the Piazza forum - responses tend to be quicker and have a wider audience. To contact the teaching staff directly, we strongly encourage you to come to office hours. If that is not possible, you can also email (non-technical questions only) to the course staff list, cs124-win1415-staff@lists.stanford.edu. We can 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-win1415-staff@lists.stanford.edu to make an appointment. For grading questions, please talk to us after class or during office hours.

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

Honor Code

Since we occasionally reuse homeworks from previous years, we expect students not to copy, refer to, or look at the solutions in preparing their answers. It is an honor code violation to intentionally refer to a previous year's solutions. This applies both to the official solutions and to solutions that you or someone else may have written up in a previous year. It is also an honor code violation to find some way to look at the test set or interfere in any way with programming assignment scoring or tampering with the submit script.

Textbooks

• There is no required textbook, but I will expect you to know the material listed above, drawn from the textbooks and other readings. The material in the readings will be tested on the final exam. Different people may learn better from different combinations of videos/lectures, reading the chapters, or coming to the in-class group exercises. The best-prepared students who do the best on the final exams tend to do all three. But I won't take roll and attendence is up to you.
  • Online new chapters from Jurafsky and Martin. third edition in progress. Speech and Language Processing. I will be giving you the PDFs.
  • Chapters from Manning, Raghavan, and Schutze. 2008. Introduction to Information Retrieval. Cambridge University Press. You can buy the book, get it from the library, or it's also available online *HERE*.

Course Description

Extracting meaning, information, and structure from human language text, speech, web pages, genome sequences, social networks, or any less structured information. Methods include: string algorithms, edit distance, language modeling, naive Bayes, inverted indices, vector semantics. 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 and 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 (or in some cases, attend the lectures that cover the identical material) 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 11:59pm Tuesday of the following week. There are no late days for review quizzes.

Class Participaton

Attendence is strongly recommended but optional except for the first day of class and 4 other lectures: 2 guest lectures and my lectures on networks and social meaning extraction. I won't be actually taking attendence but I'll being covering material that is not presented in the textbook or video lectures, and I will test this material on the final. Since lectures are on-line, the in-class sessions will be used mainly for group problem-solving, reviews, and occasional backup-lectures re-covering the video material. You can get credit for class participation by helpful answers on the class forum, asking good question of the invited speakers, helping out other students in office hours, etc.

Programming Assignments

6 programming assignments (in Java or Python, your choice). Each assignment is due at 5:00pm on the Friday it is due.

Programming Assignment Collaboration: You may talk to anybody you want about the assignments and bounce ideas off each other. But you must write the actual programs yourself.

Late homeworks

You have 4 free late (calendar) days to use on programming assignments 1-5. For the group homework PA 6, the number of late days is the mean of the late days of each person in your group, all fractions rounded up. (e.g., if your 3 members have 0, 1, and 3 late days left, your team will have 4/3 = 1.3 rounded up to 2 late days). Once these are exhausted, any PA 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. However, no assignment will be accepted more than four days after its due date.

Readings

This class has a significant amount of textbook reading. Most weeks have around 30 textbook pages. The homeworks and exams will be based heavily on the readings.

Final exam:

Wednesday Mar 18, 12:15pm-3:15pm, Hewlett 200

Final grade

• 57% homeworks
• 29% final exam
• 9% weekly review quizzes
• 5% participation in forums and class