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Overview
Mathematics & Statistics (Sci) : Linear algebra in real coordinate space: eigenvalues and diagonalization, applications; orthogonality, Gram-Schmidt process, orthogonal projection; spectral theorem for symmetric matrices; singular value decomposition; positive definite matrices. Multivariable calculus: partial derivatives; linear and quadratic approximation; directional derivatives and gradient; classification of extreme values; constrained optimization. Examples and applications in data science.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
