## SE201 : Linear Algebra (선형대수학)

This is an introductory course on linear algebra. Linear algebra studies systems of linear equa- tions and properties of vectors and matrices, and is useful in natural science and engineering, economics, social science, and especially in machine learning and optimization. I will introduce basic concepts and properties in linear algebra and matrix theory, as well as how to compute matrix algebra by Python programming.

__Linear algebra algorithms__: LU-decomposition, Gauss-Jordan elimination, Gram-Schmidt process__Basic definition of linear algebra__: rank, determinant, transformation__Vectors and vector spaces__: basis, orthogonality, orthogonal complement, column and row spaces, null and left null spaces__Eigenvalues and eigenvectors__: diagonalization, Jordan form, singular value decomposition__Applications__: solving systems of 1st order ordinary differential equations, Principal component analysis, the simplex method, natural language processing via Python.