• A course that teaches Linear Algebra with a focus on applications in computer science.
    • Fun and practical (blu3mo)

Topics covered: Introduction, vectors, Numpy

  • Although many real-life scenarios are not linear, they can be approximated using linear functions.
    • Approximating with linear functions allows the use of various tools in linear algebra, which is advantageous.

Topics covered: Matrices, matrix operations, linear equations, Gaussian elimination, vector spaces, solving Ax=b, independence, basis, and dimension, linear transformations, Exam 1, orthogonal projections, Gram-Schmidt, least squares, linear regression, determinants, eigenvalues/eigenvectors, diagonalization, dynamical systems, symmetric matrices, quadratic forms, SVD, PCA, TBD, Exam 2