Unlock: Linear Independence

A set of vectors is linearly independent if no vector is a redundant copy of the others. The concept underwrites basis, dimension, rank, the column-space test for $Ax = b$, and every overdetermined-versus-underdetermined diagnosis in linear regression and gradient-based optimization.