CSC 4510/9010: Machine Learning
Dr. Paula Matuszek
Adjunct Professor, Villanova
E-mail: Paula.Matuszek@villanova.edu or Paula.Matuszek@gmail.com
Phone: (610) 647-9789
TA: Kambagiri Atte, email@example.com
Grading and Assignments for CSC 9010.
Grading will be based on assignments, exams, a research paper presentation, and a project.
Homework assignments. These will be homework assignments and exercises which are designed to give you experience with various aspects of machine learning and Weka. 25% of grade.
Exams. There will be a midterm and final covering the material we cover in class and labs, including a few questions about presentations made by other students. The final will be comprehensive. 25%, 30% of grade.
Presentation. Machine Learning is a fast-moving area and there are many interesting projects and tools being developed. Choose a current application (published in the last two years), prepare a one-page written summary, and present it to the class. The report should include a summary of the paper(s) and a discussion of the usefulness of the work reviewed. The presentation should teach the class about the content of the paper. 10% of grade.
Project. This will be a team project involving choosing an interesting machine learning question, finding relevant data, using Weka to answer the question, writing it up, and presenting it to the class. The writeups will be individual; the presentation will be as a group. 10% of grade.
Submitting Assignments: Some assignments will be demonstrated in class on the due date and some will be submitted. I will let you know for each assignment.