Information

Where to get all official information

We plan to use lecture and this homepage as the main distribution points of information, and crucial time-sensitive announcements will be announced either in lecture or via email. (Hence, we won't use CMS for announcements, and you don't absolutely need to look at Piazza, although we recommend signing up for and monitoring the course Piazza page, whose link is given above.)

Course time and location

Tuesdays and Thursdays, 10:10-11:25am, Phillips Hall 101

Getting help or talking to someone

Feel free to ask questions on Piazza, where multiple people can participate and benefit! But we also have a great couse staff to assist you, as well. Office hours are listed below. (None held during official Cornell breaks unless otherwise noted.)

Name Contact info (***=@gmail.com,**=@cs.cornell.edu; *=@cornell.edu) Office Hours
Prof. Karthik Sridharan sridharan**
424 Gates Hall

Wednesday 2-3:00pm

TA Esin Durmus ed459*

Tuesday 5:30-6:30pm, Gates G11

 

TA Vlad Niculae vn66*

Thursday 1-2pm, Gates G17

TA Jonathan Simon js3268*

Wednesday 10:30-11:30am, Gates G19

TA Ashudeep Singh as3354*

Monday 4-5pm, Gates G15, Gates G15

TA consultant Yu Sun yueatsprograms***

Fridays 11am-12pm, Gates G13

TA Jeff Tian yt336*

Friday 3-4pm, Gates G17

TA Felix Wu fw245*

Text

There is no required textbook, given the coverage of the class. We expect to post recommended readings when appropriate.

Coursework

Currently, we are planning roughly three to five assignments (some combination of pencil-and-paper and programming, in whatever language you wish to use) and two major programming projects (which we'll be running as “competitions” for fun, but your grades will be determined by proficiency, not by how you rank!), including a final project. No exams are planned.

Here is a list of other machine learning courses at Cornell.

Academic Integrity

We distinguish between “merely” violating the rules for a given assignment and violating the principles of academic integrity. Academic and scientific integrity compels one to properly attribute to others any work, ideas, or phrasing that one did not create oneself. To do otherwise is fraud.

We emphasize certain points here. The way to avoid violating academic integrity is to always document any portions of work you submit that are due to or influenced by other sources even if those sources weren't permitted by the rules. The worst-case outcome for merely breaking the rules is a grade penalty; the worst-case scenario in the fraud scenario is academic-integrity hearing procedures (on top of grade penalties).

A general rule of thumb is to acknowledge the work and contributions and ideas and words and wordings of others. Do not copy or slightly reword portions of papers, Wikipedia articles, textbooks, other students' work, something you heard from a talk or a conversation, or anything else, really, without acknowledging your sources. See http://www.cs.cornell.edu/courses/cs6742/2011sp/handouts/ack-others.pdf

(We make an exception for sources that can be taken for granted in the instructional setting, namely, the course materials. To minimize documentation effort, we also do not expect you to credit the course staff for ideas you get from them, although it's nice to do so anyway.)

For more information on Cornell's policies, see http://www.theuniversityfaculty.cornell.edu/AcadInteg/

I take violations of the Code of Academic Integrity and the principles behind it very seriously, and have assigned failing grades for such violations in the past.