Home Staff Lectures Assignments

Winter 2024 Announcement

We are keeping the class 100% remote, just like it was for Winter 2021/2022/2023 (including office hours, quizzes, etc.). Attendance will remain 100% optional the entire quarter.

Some TAs may hold some in-person office hours.

Please join Ed for announcements throughout the term!


A survey of numerical approaches to the continuous mathematics used throughout computer science with an emphasis on machine and deep learning. Although motivated from the standpoint of machine learning, the course will focus on the underlying mathematical methods including computational linear algebra and optimization, as well as special topics such as automatic differentiation via backward propagation, momentum methods from ordinary differential equations, CNNs, RNNs, etc. Written homework assignments and (straightforward) quizzes focus on various concepts.

This course replaces 205A and satisfies all similar requirements.

A Motivational Thought

"Everyone is sure of this [that errors are normally distributed], Mr. Lippman told me one day, since the experimentalists believe that it is a mathematical theorem, and the mathematicians that it is an experimentally determined fact."--Henri Poincaré

General Info

Course Policy