what do you mean by rank and kernel
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Rank---In linear algebra, the rank of a matrix A is the dimensions of the vector space generated (or spanned) by its columns.This corresponds to the maximal number of linearly independent columns of A. This, in turn, is identical to the dimension of the space spanned by its rows.
Kernal---, the kernel (also known as null space or nulls space) of a linear map L : V → W between two vector spaces V and W, is the set of all elements v of V for which L(v) = 0, where 0 denotes the zero vector in W.
Rank---In linear algebra, the rank of a matrix A is the dimensions of the vector space generated (or spanned) by its columns.This corresponds to the maximal number of linearly independent columns of A. This, in turn, is identical to the dimension of the space spanned by its rows.
Kernal---, the kernel (also known as null space or nulls space) of a linear map L : V → W between two vector spaces V and W, is the set of all elements v of V for which L(v) = 0, where 0 denotes the zero vector in W.
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