NOTE: WE CURRENTLY DO NOT HAVE A TIME SCHEDULED FOR THIS COURSE. INFORMATION WILL BE SENT ASAP TO ALL STUDENTS WHO HAVE APPLIED.
This DeCal is intended for any student interested in the mathematics behind machine learning models, and particularly those who meet the math prerequisites for CS 189 but want to become more comfortable with the material and its applications to machine learning. The course assumes general knowledge in linear algebra, vector calculus, optimization problems, and statistics; however, students do not need to feel like experts in any of these fields to take this course. We will give general descriptions of things like vector spaces and random variables, but will not cover all of the important results from these fields. Rather, we will focus on the results which have the most direct applications to machine learning, and will go over some of these applications so they are more familiar when encountered in CS189.
There will be weekly homework, graded on completion (not correctness). Lecture attendance is mandatory; students may miss up to two lectures unexcused, and must request excuses in advance for any further missed lectures. There are no quizzes or tests.
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