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In this program

Sparse matrix formats
Memory-aware implementations
Parallel and distributed linear algebra (overview)
Least squares
Ridge regression at scale
Randomized numerical linear algebra (sketching, introduction)
Applications in data science and imaging
PDE discretizations

Large-scale and applied problems

Applications in data science and imaging

Numerical linear algebra · STEM / applied

Topic

Applications in data science and imaging

Practice by unit: Large-scale and applied problems

Graduate Numerical Linear Algebra — scope drawn from open NLA notes (e.g. Trefethen/Bau-style OER mirrors) and typical US graduate NLA syllabi.

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