CSCI8363
CSCI 8363 - Numerical Linear Algebra in Data Exploration (3 Cr.)
Computer Science and Engineering Administration (11108)
TIOT - College of Science and Engineering
CSCI 8363 - Numerical Linear Algebra in Data Exploration (3 Cr.)
Course description
Computational methods in linear algebra, matrix decompositions for linear equations, least squares, eigenvalue problems, singular value decomposition, conditioning, stability in method for machine learning, large data collections. Principal directions, unsupervised clustering, latent semantic indexing, linear least squares fit. Markov chain models on hyperlink structure.
prereq: 5304 or instr consent
prereq: 5304 or instr consent
Minimum credits
3
Maximum credits
3
Is this course repeatable?
No
Grading basis
OPT - Student Option
Lecture
Fulfills the writing intensive requirement?
No
Typically offered term(s)
Periodic Spring