CSC 4510/9010: Applied Machine Learning
Mendel G88, Fall, 2016
Dr. Paula Matuszek
Adjunct Professor, Villanova
Office: Mendel 288.
E-mail: Paula.Matuszek@villanova.edu or Paula.Matuszek@gmail.com
Phone: (610) 647-9789
TA: Shiva Beesu
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 take about 20 minutes and should teach the class something about the content of the paper. 10% of grade.
Project. This will be a 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. This can be done as an individual or as part of a group. 10% of grade.