A resource enables the determination of the null space of a matrix, also known as the kernel. The null space comprises all vectors that, when multiplied by the given matrix, result in the zero vector. For example, if a matrix A multiplied by a vector x equals the zero vector, then x is an element of the null space of A.
This computation is fundamental in linear algebra, with applications spanning across various fields such as data analysis, computer graphics, and solving systems of linear equations. Its utility lies in understanding the properties and behavior of linear transformations represented by matrices. Historically, finding the null space of a matrix was a laborious manual process, but these automated solutions have significantly enhanced efficiency and accessibility.