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In machine learning, the term tensor informally refers to two different concepts (i) a way of organizing data and (ii) a multilinear (tensor) transformation. Data may be organized in a multidimensional array (M-way array), informally referred to as a "data tensor"; however, in the strict mathematical sense, a tensor is a multilinear mapping over a set of domain vector spaces to a range vector ...
De facto standard for matrix/tensor operations in Python. Pandas , a library for data manipulation and analysis. SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more.
Tensor [4] is a tensor package written for the Mathematica system. It provides many functions relevant for General Relativity calculations in general Riemann–Cartan geometries. Ricci [5] is a system for Mathematica 2.x and later for doing basic tensor analysis, available for free.
A metric tensor is a (symmetric) (0, 2)-tensor; it is thus possible to contract an upper index of a tensor with one of the lower indices of the metric tensor in the product. This produces a new tensor with the same index structure as the previous tensor, but with lower index generally shown in the same position of the contracted upper index.
More generally, a multidimensional array type can be called a tensor type, by analogy with the physical concept, tensor. [ 2 ] Language support for array types may include certain built-in array data types, some syntactic constructions ( array type constructors ) that the programmer may use to define such types and declare array variables, and ...
[20] [21] [18] [19] The first character of all TIO codes is a \, followed by two other ASCII characters vaguely resembling the glyph to be substituted. [ 20 ] [ 21 ] [ 18 ] [ 19 ] [ 22 ] All other characters can be entered using the special \nnn TIO code syntax with nnn being a three-digit decimal number (with leading zeros if necessary) of the ...
JAX is a machine learning framework for transforming numerical functions. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).
If the two coordinate vectors have dimensions n and m, then their outer product is an n × m matrix. More generally, given two tensors (multidimensional arrays of numbers), their outer product is a tensor. The outer product of tensors is also referred to as their tensor product, and can be used to define the tensor algebra.