Rank (linear algebra)
In the realm of Linear Algebra, the rank of a Matrix is a fundamental concept that describes the maximum number of Linearly Independent rows or columns in the matrix. It is a measure of the "non-degenerateness" of the matrix, and is closely related to the concept of Determinant. The rank of a matrix can be computed using various methods, including Gaussian Elimination and Singular Value Decomposition. Understanding the rank of a matrix is crucial in many applications, including Convolution and Polynomial Regression. The concept of rank is also closely tied to the idea of Scalars and Euclidean spaces.