In this course, you will learn the fundmental theory and applications of linear algebra. The topics of interests include the concept of vector spaces and matrix algebra, and some other advanced features regarding the eigenvalues/eigenvectors, orthogonality, leastsquares approximation, and geometric transformation, etc.

- David C. Lay, Linear Algebra and Its Applications, 4th edition, Pearson Education Limited, 2014. (5th edition, 2016)
- 課程講義(投影片)

- Howard Anton and Chris Rorres, Elementary Linear Algebra, 11th edition, John Wiley & Sons, 2015.
- Ward Cheney and David Kincaid, Linear Algebra, Theory and Applications, 2nd edition, Jones & Bartlett Learning, 2012.
- Gilbert Strang, Linear Algebra and Its Applications, 4th edition, Thomson Brooks/Cole.

- Linear Equations in Linear Algebra
- Matrix Algebra
- Determinants
- Vector Spaces
- Eigenvalues and Eigenvectors
- Orthogonality and Least Squares
- Symmetric Metrices and Quadratic Forms
- The Geometry of Vector Spaces

- Class Information(Update on 2022/02/14)
- Chapter 0: Linear algebra
- Chapter 1.a: Linear Equations in Linear Algebra(Update on 2021/04/14)
- Chapter 1.b: Linear Equations in Linear Algebra(Update on 2021/04/14)
- Chapter 2.a: Matrix algebra(Updated on 2021/04/14)
- Chapter 2.b: Matrix algebra(Updated on 2021/04/14)
- Chapter 3: Determinants(Updated on 2021/04/14)
- Chapter 4.a: Vector spaces(Updated on 2021/04/14)
- Chapter 4.b: Vector spaces(Updated on 2021/04/14)
- Chapter 5: Eigenvalues and eigenvectors(Updated on 2021/05/29)
- Chapter 6.a: Orthogonality and least-squares(Updated on 2021/05/29)
- Chapter 6.b: Orthogonality and least-squares(Updated on 2021/05/29)
- Chapter 7: Symmetric matrices and quadratic forms(Updated on 2021/05/29)

- None

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廖峻浩 Email: jiunnhaw0823@gmail.com