🧮Implementations of numerical linear algebra algorithms including Cholesky, LU Decomposition, ESOR, PSD check, and QR using Householder reflections, as part of the Linear Numerical Algebra ΘΠ03 ...

NumPy includes some tools for working with linear algebra in the numpy.linalg module. However, unless you really don’t want to add SciPy as a dependency to your project, it’s typically better to use ...

This is the revised and expanded edition of the problem book Linear Algebra: Challenging Problems for Students, now entitled Problems in Linear Algebra and Matrix Theory.This new edition contains ...

When you take a digital photo with your phone or transform the image in Photoshop, when you play a video game or watch a movie with digital effects, when you do a web search or make a phone call, you ...

The book consists of three parts. Part 1 focuses on vectors and their manipulation. Vector algebra, linear functions, linearization, inner products, norms, linear independence, the concept of a basis, ...

For those interested in using linear algebra in a symbolic setting, or for working with matrices over the integers or rational numbers (not float point numbers) you'll be interested in using the SymPy ...