In Part 1 of this blog, I had explained what tensors are and some related terminology. Just to briefly recap, a tensor is a multidimensional array of numbers. Tensors provide a useful representation for data that involves multiple modalities of sensing or the data has multiple aspects in terms of time or space or both. In this and the next post, we are going to look at tensor decomposition and suggest some applications of tensor decomposition.
Please visit the complete post at
https://iksinc.tech/understanding-tensors-and-tensor-decompositions-part-2/(opens in a new tab)
From Data to Decisions 