linear transformations

The first lecture of Gilbert Strang's MIT 18.06 Linear Algebra course, covering the geometry of linear equations. It opens a full 35-lecture university course.

Sasha Rush surveys linear RNNs and state space models as replacements for attention in transformer-style models, in a talk for MLSys. It covers the foundational preliminaries and predates Mamba.

The introductory lecture of Stephen Boyd's Stanford Convex Optimization I course (EE 364A). It outlines convex sets, functions and problems, and the course's coverage of least-squares, linear and semidefinite programming, duality and interior-point methods.

The opening lecture of Steve Brunton's Control Bootcamp, covering the kinds of control and why closed-loop feedback matters. It starts a series that follows the control chapter of the Brunton and Kutz data-driven science book.

Leonard Susskind opens Stanford Continuing Studies' Theoretical Minimum series with an introduction to quantum mechanics, a course for people who want real physics rather than popularization. It assumes some calculus and linear algebra.

Guy Kawasaki's UC Berkeley Haas talk on the top ten mistakes entrepreneurs make, covering a startup from inception to exit.