You will summarize your project results in a written report and an oral presentation. If your project involves an implementation, then you may be asked to also give a brief demonstration. The written report must use a professional writing style similar to that found in an ACM or IEEE journal, including abstract, introduction, summary of related work, your contribution, references, and an appendix (if necessary). The oral presentation will be to the entire class at the end of the semester: during dead week (December 10-14), and if necessary, during the week prior to dead week (December 3-7). You will submit your written report to me no later than December 14 (the last day of dead week). In accordance with UNL dead week policies, you have now been informed in writing of the nature and scope of this project prior to the eighth week of classes.
Suggestions for projects can be found on the course's web pages, but you may propose your own topic as well. You must receive my approval on your topic before proceeding with your work! To be a valid topic, it must go beyond the scope of the course. So your project could be on a topic we did not cover in class at all, or could more deeply explore a topic we covered in class.
Rules on projects, a.k.a. what to turn in for your final project writeup
Tips on Presenting Technical Material
Schedule of this semester's project presentations
Topic surveys or implementations of existing
systems
Research projects: If your thesis research or a project you are doing
for another course is appropriate for this course's project, I may allow you to
use it for this course
Project ideas from offerings of Machine Learning
courses at other institutions
A
survey paper by Tom Dietterich on current research directions in machine
learning [from AI Magazine, vol. 18, no. 4, pp. 97-136]
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Last modified 16 August 2011; please report problems to sscott AT cse.