Coding the Matrix: Linear Algebra through Applications to Computer Science

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An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program.

Mathematical concepts and computational problems are motivated by applications in computer science. The reader learns by doing, writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications.

Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. A companion web site, codingthematrix.com provides data and support code.

Most of the assignments can be auto-graded online. Over two hundred illustrations, including a selection of relevant xkcd comics. Chapters: The Function, The Field, The Vector, The Vector Space, The Matrix, The Basis, Dimension, Gaussian Elimination, The Inner Product, Special Bases, The Singular Value Decomposition, The Eigenvector, The Linear Program

There used to be a Coursera course called Coding the Matrix. It covered many linear algebra topics using Python. The course isn't available anymore on Coursera anymore, but you can still buy the textbook:

https://www.amazon.com/Coding-Matrix-Algebra-Applications-Co...

If you want to learn linear algebra by coding in python, this is hands down the best book out there.

Coding the Matrix - Philip Klein [0]

It used to have a Coursera course, but I think it's been taken down. The website has videos of the course taught at Brown I think.

The associated website is: https://www.amazon.com/Coding-Matrix-Algebra-Applications-Co...

If you haven't already studied Linear Algebra, and want to get a headstart on that, check out the "Coding The Matrix" book/videos from Brown.

https://www.amazon.com/Coding-Matrix-Algebra-Applications-Co...

Also, see the Gilbert Strang video series on Linear Algebra: