Class
meets: TF 10:20-11:40am, Hill-005.
Office Hours: TF9-10am, or by appointment.
Email:
zchan at math dot rutgers dot edu
Canvas: The course will use
Canvas for all material during the semester.
All enrolled students should
have automatic access to the site after logging in to Canvas.
Current information about syllabus,
homework assignments and exams
will be found there.
Some General Comments: We will mostly use Linear Algebra and Learning from Datainear Algebra and Optimization for Machine Learning by Gilbert Strang, but may use other sources when appropriate.
It is assumed that students have had a basic course on linear algebra and are familiar with the basic matrix operations. The course will focus on concepts that are at a more advanced level, so will largely leave to the students to review the material dealing with basic matrix operations. Some review/practice problems on some basic linear algebra material have been posted in the course canvas site.
Homework Assignments and Grading Policy: The grade for the course will be based on a combination of graded homework problems and quizzes, up to two midterm exams and a final exam (possibly with a component of a project/presentation). Here is the break up: