MATH 464: Linear Algebra with Data Applications

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Course Information from the University Catalog

Credits: 3

Structure of linear spaces and the operator algebra, duality, invariants, Jordan and singular value decompositions, spectral theorem. Rigorous derivation of foundational data science methods such as PCA, MDS, and SVM. Computational and analytic assignments are given. Offered by Mathematics. Limited to three attempts.

Registration Restrictions:

Required Prerequisites: ((MATH 322^C or 322^XS) and (CS 112^C or 112^XS)).
^C Requires minimum grade of C.
^XS Requires minimum grade of XS.

Schedule Type: Lecture

Grading:
This course is graded on the Undergraduate Regular scale.