CSCI 8363: Numerical Linear Algebra in Data Exploration

3 Credits

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

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All Instructors

A- Average (3.795)Most Common: A (50%)

This total also includes data from semesters with unknown instructors.

28 students
SWFDCBA
  • 4.29

    /5

    Recommend
  • 4.00

    /5

    Effort
  • 4.29

    /5

    Understanding
  • 4.32

    /5

    Interesting
  • 3.50

    /5

    Activities


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