The Deep Learning Book Series is a set of 12 blog posts and Python notebooks going through the chapter on linear algebra from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016).

1. Scalars, Vectors, Matrices and Tensors

2. Multiplying Matrices and Vectors

3. Identity and Inverse Matrices

4. Linear Dependence and Span

5. Norms

6. Special Kinds of Matrices and Vectors

7. Eigendecomposition

8. Singular Value Decomposition

9. The Moore-Penrose Pseudoinverse

10. The Trace Operator

11. The Determinant

12. Principal Components Analysis (PCA)