Solutions to Mike X Cohen`s "Practical Linear Algebra for Data Science"
Link to the book on amazon
- Vectors, Part 1
- Vectors, Part 2
- Vector Applications
- Matrices, Part 1
- Matrices, Part 2
- Matrix Applications
- Matrix Inverse
- Orthogonal Matrices and QR Decomposition
- Row Reduction and LU Decomposition
- General Linear Models and Least Squares
- Least Squares Applications
- Eigendecomposition
- Singular Value Decomposition
- Eigendecomposition and SVD Applications