Lesson 14 of 16
Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra
Lessons16 lessons
- 1Vectors | Chapter 1, Essence of linear algebra
- 2Linear combinations, span, and basis vectors | Chapter 2, Essence of linear algebra
- 3Linear transformations and matrices | Chapter 3, Essence of linear algebra
- 4Matrix multiplication as composition | Chapter 4, Essence of linear algebra
- 5Three-dimensional linear transformations | Chapter 5, Essence of linear algebra
- 6The determinant | Chapter 6, Essence of linear algebra
- 7Inverse matrices, column space and null space | Chapter 7, Essence of linear algebra
- 8Nonsquare matrices as transformations between dimensions | Chapter 8, Essence of linear algebra
- 9Dot products and duality | Chapter 9, Essence of linear algebra
- 10Cross products | Chapter 10, Essence of linear algebra
- 11Cross products in the light of linear transformations | Chapter 11, Essence of linear algebra
- 12Cramer's rule, explained geometrically | Chapter 12, Essence of linear algebra
- 13Change of basis | Chapter 13, Essence of linear algebra
- 14Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra
- 15A quick trick for computing eigenvalues | Chapter 15, Essence of linear algebra
- 16Abstract vector spaces | Chapter 16, Essence of linear algebra