| Fall Term 2024 Advanced Linear Algebra for Data Science - 5961 - MATH 355 |
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Prerequisites/Notes: Math 250: Linear Algebra Catalog Description : Covers advanced topics in linear algebra, with applications to data science. Possible topics include matrix factorizations LU, QR, SVD, and CMR, applications to PCA (principal component analysis), dimensionality reduction, weighted least squares and other forms of interpolation, the DFT and FFT, spectral graph drawing and spectral clustering from the Laplacian and modularity matrices, Kalman filters, covariance matrices, multivariate Gaussians, Markov chains, and matrix completion. The choice of topics depends on the instructor. Will use both exams and project-based assessment. Students will apply linear algebra to concrete data sets for their projects. PREREQUISITES: Math 250: Linear Algebra Attributes: 200-399 Foundation/Gateway Crs
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