MATH 104: Applied Matrix Theory
Linear algebra for applications in science and engineering: orthogonality, projections, spectral theory for symmetric matrices, the singular value decomposition, the QR decomposition, least-squares, the condition number of a matrix, algorithms for solving linear systems. (
Math 113 offers a more theoretical treatment of linear algebra.) Prerequisites:
Math 51 and programming experience on par with CS106nnMath 104 and
EE103/CME103 cover complementary topics in applied linear algebra. The focus of
Math 104 is on algorithms and concepts; the focus of EE103 is on a few linear algebra concepts, and many applications.
Terms: Aut, Win
| Units: 3
| UG Reqs: GER:DB-Math
Instructors:
Feldheim, O. (PI)
;
Ying, L. (PI)
;
Dore, D. (TA)
;
He, X. (TA)
;
McConnell, S. (TA)
;
Safaee, P. (TA)
;
Velcheva, K. (TA)
;
Wigderson, Y. (TA)
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