  We present an overview of the key ideas and skills necessary to begin
implementing tensor network methods numerically, which is intended to
facilitate the practical application of tensor network methods for researchers
that are already versed with their theoretical foundations. These skills
include an introduction to the contraction of tensor networks, to optimal
tensor decompositions, and to the manipulation of gauge degrees of freedom in
tensor networks. The topics presented are of key importance to many common
tensor network algorithms such as DMRG, TEBD, TRG, PEPS and MERA.
