Linear Algebra and Optimization for Machine Learning - Charu C. Aggarwal

1. Linear Algebra and Optimization - An Introduction

2. Linear Transformations and Linear Systems

3. Eigenvectors and Diagonalizable Matrices

4. Optimization Basics: A Machine Learning View

5. Advanced Optimization Solutions

6. Constrained Optimization and Duality

7. Singular Value Decomposition

8. Matrix Factorization

9. The Linear Algebra of Similarity

10. The Linear Algebra of Graphs

11. Optimization in Computational Graphs