Tensor Spaces and Numerical Tensor Calculus Part I: Algebraic Tensors Introduction Matrix Tools Algebraic Foundations of Tensor Spaces Part II: Functional Analysis of Tensor Spaces Banach Tensor Spaces General Techniques Minimal Subspaces. Part III: Numerical Treatment r Term Representation Tensor Subspace Represenation r Term Approximation Tensor Subspace Approximation. Hierarchical Tensor Representation Matrix Product Systems Tensor Operations Tensorisation Generalised Cross Approximation Applications to Elliptic Partial Differential Equations Miscellaneous Topics References Index. Special numerical techniques are already needed to deal with nxn matrices for large n. Tensor data are of size nxnx...xn=n^d where n^d exceeds the computer memory by far. They appear for problems of high spatial dimensions. Since standard methods fail a particular tensor calculus is needed to treat such problems. The monograph describes the methods how tensors can be practically treated and how numerical operations can be performed. Applications are problems from quantum chemistry approximation of multivariate functions solution of pde e.g. with stochastic coefficients etc.