Dr. Eick
Due date: In general, you should be done with Project1 before Spring break; however, your report is due on We., March 14 for groups who present on April 4, and on Fr., March 16 for groups who present on April 2) and the talk slides are due 2 days before your presentation.
Last updated: Feb. 11, 6p
This course project is an opportunity for you to explore an interesting machine learning problem of your choice in the context of a real-world data set. The idea is to apply multiple machine learning techniques/variations of a single approach to a dataset, to compare the results, and to summarize your findings in a report and to share your project findings with your class mates in a 13-minute presentation early April 2013. The project is a group project with preferably two students in each group. In your course project you can't use results you have developed in previous research or former course projects. As far as project themes are concerned, hints will be given in the lecture; moreover, other machine learning courses give very similar projects; therefore, checking the webpages of other machine learning courses might help you finding interesting data sets/project themes:
 http://select.cs.cmu.edu/class/10701-F09/projects.html
 http://courses.csail.mit.edu/6.867/wiki/index.php?title=Project
 http://www.cs.cmu.edu/~aarti/Class/10601/proj.shtml
 http://www.cs.cmu.edu/~epxing/Class/10701/project.html
 http://comminfo.rutgers.edu/conferences/mmchallenge/
 http://www.cs.cornell.edu/courses/cs6780/2010fa/projects_2010.html
This is the timeline for Project1 (all deadlines are 11p):
Feb. 13: Form Groups
Feb: 17: Submit 1-page Project Description for Approval
March 1: Submit 2-page Progress Report (will count 10% towards your project grade)
March 14/16: Submit 6-8 page Project Report (in ACM(-SIGKDD-format))
March 31/April 2: Submit talk slides to Zechun
April 2/4: Project1 Student Presentation
Please submit the following information in your 1-page draft project description (due Feb.
17, 11p):
1.
Names
2.
Project Title
3.
Dataset Used
4.
Project Idea (use 2 paragraphs)
5.
Software you will write and/or use are
6.
List of Papers to read that relevant for your project
7.
Project Milestones
8.
Project Completion Plan
.
Your project description can be sketchy with respect to items 5-8. The progress report, you deliver on March 1, should address items 5-8 in much more details.
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