# Linear Algebra

I am reviewing Linear Algebra as a part of my doctoral program, and as such, I will be sharing my programming notes here. And this means that this course is intended only for my personal consumption; although others are free to avail themselves of my notes and all the related materials that will be posted under this link. The book that I am using is Linear Algebra by David Cherney, Tom Denton, Rohit Thomas and Andrew Waldron (2013).

# Objective

To learn how to solve Linear Algebra problems with Python.

Topics

- What is Linear Algebra?
- Systems of Linear Equations
- The Simplex Method
- Vectors in Space, n-Vectors
- Vector Spaces
- Linear Transformation
- Matrices
- Determinants
- Subspaces and Spanning Sets
- Linear Independence
- Basic and Domension
- Eigenvalues and Eigenvectors
- Diagonalization
- Orthonormal Bases and Complements
- Diagonalizing Symmetric Matrices
- Kernel, Range, Nullity, Rank
- Least Squares and Singular Values

### Citation

For attribution, please cite this work as

Reng (2019, Jan. 4). Reng Data Science Institute: Linear Algebra. Retrieved from https://www.rengdatascience.io/posts/2019-01-04-linear-algebra/

BibTeX citation

@misc{reng2019linear,
author = {Reng, Alier Ëë},
title = {Reng Data Science Institute: Linear Algebra},
url = {https://www.rengdatascience.io/posts/2019-01-04-linear-algebra/},
year = {2019}
}