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MATH 334 Computational Linear Algebra 6 credits
Computational linear algebra is full of ideas that are useful when interpreting linear algebra objects as data. This course develops these ideas with a balance of theory, applications, and algorithms. Topics will be selected from singular value decomposition, LU and QR factorization, orthogonal computation, conditioning, numerical stability, eigenvalue approximation and iterative methods. Applications include interpolation, least squares, low rank approximation, principal component analysis, regularization, data classification, image processing, and selected topics from machine learning.
Not open to students who have taken MATH 332 – Advanced Linear Algebra Fall 2023 or Fall 2025.
- Fall 2026
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): MATH 236 with a grade of C- or better or received a Carleton Mathematics 236 Requisite Equivalency. NOT open to students who have taken MATH 332 – Advanced Linear Algebra Fall 2023 or Fall 2025.