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Linear algebra for data science, chapter 13 exercise 6 (create random matrices with any eigenvalues)
Linear algebra for data science, chapter 13 exercise 10 (orthogonality of generalized eigenvectors)
Lecture13: 2.1 Numerical Linear Algebra Part I, Math 405: Learning From Data.
Linear algebra for data science, chapter 11 exercise 5 (matrix inverse as a least-squares problem)
Linear algebra for data science, chapter 5 exercise 4 (adding matrices element-wise)
Linear algebra for data science, chapter 13 exercise 4 (complex eigvals of random mats on a circle)
Linear algebra for data science, chapter 3 exercise 3 (visualizing subspaces)
Linear algebra for data science, chapter 13 exercise 2 (use geometry to find a code bug)
Linear algebra for data science, chapter 9 exercise 5 (more on inversion inaccuracies)
Linear algebra for data science, chapter 10 exercise 5 (AtA, LU, and permutation matrices)
Linear algebra for data science, chapter 13 exercise 8 (random data with specified correlations)
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Last Updated: August 15, 2026
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