Syllabus Information |
Fall 2024
Jan 30, 2025 |
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| DL 0052M - Ortho Symmetric Matrices SVD |
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Associated Term:
Fall 2024
Learning Objectives: • Orthogonal projections and distances to express a vector as a linear combination of orthogonal vectors • How to construct vector approximations using projections • How to characterize bases for subspaces, and construct orthonormal bases • The iterative Gram Schmidt Process • The QR decomposition • Orthogonal basis construction • How to compute general solutions and least squares errors to least squares problems using the normal equations and the QR decomposition • How to apply least-squares and multiple regression to construct a linear model from a set of data points • A spectral decomposition of a matrix • Quadratic forms using eigenvalues and eigenvectors • The SVD for a rectangular matrix Required Materials: Internet connection (DSL, LAN, or cable connection desirable) Adobe Acrobat PDF reader (to download for free, visit get.adobe.com/reader/) Technical Requirements: |
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