18.S096 | January IAP 2023 | Undergraduate

Matrix Calculus for Machine Learning and Beyond

Lecture 5 Part 1: Derivative of Matrix Determinant and Inverse

Description: The first ~6 minutes are on the topic Norms and Derivatives: Why a norm of the input and output are needed to define a derivative.  Now we can find the “matrix gradient” of the determinant function (leading to the “adjugate” matrix), and the “Jacobian” of a matrix inverse.

Instructors: Alan Edelman, Steven G. Johnson

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January IAP 2023
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