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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the Singular Value Decomposition (SVD) of matrices, explaining how any matrix can be decomposed into a sum of matrices using its eigenvalues and eigenvectors. The lecture details the process of transforming vectors through matrices, illustrating the concept with examples and discussing the implications of SVD in matrix operations.