MIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023
Instructors: Alan Edelman, Steven G. Johnson
View the complete course: https://ocw.mit.edu/courses/18-s096-matrix-calculus-for-machine-learning-and-beyond-january-iap-2023/
YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62EaLLH92E_VCN4izBKK6OE
Description: Nonlinear root finding by Newton’s method and optimization by gradient descent. “Adjoint” methods (reverse-mode/backpropagation) lets us find gradients efficiently for large-scale engineering optimization.
License: Creative Commons BY-NC-SA
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