MATH 2170 - Applied Linear Algebra

Institution:

Southern Utah University

Subject:

Mathematics

Description:

An introduction to linear algebra, with emphasis on data science and machine learning. Topics include vectors, inner products, norms, linear independence, orthonormal sets, Gram-Schmidt algorithm, clustering and the k-means algorithm, linear systems, matrix algebra, matrix inverses, linear and affine transformations, linear dynamical systems, least-squares, data fitting, eigenvalues, and singular value decomposition. Additional applications may include QR factorization, adjacency matrices and network flow, computer graphics, regularization, cross-validation, classification, constrained least-squares, time-series prediction, linear quadratic control, dimensionality reduction, principal component analysis, and portfolio optimization. Students will use Python throughout this course. (Fall, Spring) [Graded (Standard Letter)]Prerequisite(s): (MATH 1100 or MATH 1210) and (ANLY 2500 or CSCY 1030 or CS 1400 or CS 1410 or instructor approval) - Prerequisite Min. Grade: CRegistration Restriction(s): None

Credits:

3.00

Credit Hours:

Prerequisites:

( MATH 1100 O MATH 1210 ) ( A ANLY 2500 O CSCY 1300 O CS 1400 O CS 1410 )

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.suu.edu/

Phone Number:

(435) 586-7700

Regional Accreditation:

Northwest Commission on Colleges and Universities

Calendar System:

Semester

General Education

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