Machine Learning (CSE 6363) Fall 1996

Course Details

The purpose of this course is to expose the student to several machine learning paradigms and provide in-depth understanding of selected methods. Homeworks will provide hands-on experience with selected learning methods and will test the student's understanding of topics discussed in class.

The class project serves to further the student's understanding of one or more methods through an experimental or theoretical analysis of the learning methods. Students are required to obtain approval on a project proposal. Ideas for projects will be distributed in class.

Each student will make a class presentation of about 30 minutes on one or more technical papers in the area of machine learning to be approved by the instructor. The presentation must demonstrate an indepth understanding of the topic, including background material from the paper's references, and provide a critical review. Longer papers tend to be more self-contained; whereas, shorter papers will require more auxiliary material.

Lastly, the student is required to participate in class by submitting brief critiques of selected papers to be covered in class and participating in class discussions. The purpose of the critiques is to stimulate critical thinking and discussions on class topics. A critique is not merely a summary, but your own reactions to the content of the reading. Critiques should be approximately one page of single spaced type.

LATE POLICY: Homeworks may be turned in up to 48 hours beyond the due date for a 10\% penalty. Only homeworks can be turned in late; all other work will receive no credit beyond the due date.

If you require an accommodation based on disability, please see me during the first week of the semester so we can be sure you are appropriately accommodated.