  This is an introductory survey, from a geometric perspective, on the Singular
Value Decomposition (SVD) for real matrices, focusing on the role of the
Terracini Lemma. We extend this point of view to tensors, we define the
singular space of a tensor as the space spanned by singular vector tuples and
we study some of its basic properties.
