A symmetric matrix is a square matrix that is equal to its transpose. This means that the matrix remains unchanged when its rows are swapped…

# Category: Linear Algebra

Extracting diagonals and calculating the trace are basic yet vital operations in linear algebra. The diagonal of a matrix refers to the set of elements…

Transposing a matrix is one of the fundamental operations in linear algebra. This operation involves flipping a matrix over its diagonal, turning the matrix’s rows…

Matrix scalar multiplication is a fundamental operation in linear algebra, where every element of a matrix is multiplied by a scalar (a constant number). This…

Matrix addition and subtraction are fundamental operations in linear algebra, allowing for the direct combination or comparison of matrix elements. These operations are critical in…

Concatenating matrices means combining two or more matrices into a single one. This can be done in two ways: horizontally or vertically. Understanding how to…

Triangular matrices come in two types: lower triangular and upper triangular. Understanding how to create these matrices in Python using NumPy can simplify many computational…

Beyond the common square and rectangular types, there are special matrices that serve unique purposes in mathematical computations and applications. The identity, zero, and diagonal…

A matrix is a collection of numbers arranged in a fixed number of rows and columns. The size or shape of a matrix is defined…

Vector normalization is the process of adjusting the length (magnitude) of a vector to 1, turning it into a unit vector. For those who need…