{"repo":"gorgonia/tensor","free":true,"listed":false,"github":"https://github.com/gorgonia/tensor","clone":"git clone https://github.com/gorgonia/tensor.git","description":"package tensor provides efficient and generic n-dimensional arrays in Go that are useful for machine learning and deep learning purposes","language":"Go","stars":382,"topics":["tensor","ndarray","multidimensional-arrays","deep-learning","machine-learning","golang","hacktoberfest"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"Package tensor # Package tensor is a package that provides efficient, generic (by some definitions of generic) n-dimensional arrays in Go. Also in this package are functions and methods that are used commonly in arithmetic, comparison and linear algebra operations. The main purpose of this package is to support the operations required by Gorgonia. Introduction ## In the data analysis world, Numpy and Matlab currently reign supreme. Both tools rely heavily on having performant n-dimensional arrays, or tensors. There is an obvious need for multidimensional arrays in Go . While slices are cool, a large majority of scientific and numeric computing work relies heavily on matrices (two-dimensional arrays), three dimensional arrays and so on. In Go, the typical way of getting multidimensional arrays is to use something like [][]T . Applications that are more math heavy may opt to use the very excellent Gonum matrix package. What then if we want to go beyond having a float64 matrix? What if we wanted a 3-dimensional float32 array? It comes to reason then there should be a data structure that handles these things. The tensor package fits in that niche. Basic Idea: Tensor ### A tensor is a multidimensional array. It's like a slice, but works in multiple dimensions. With slices, there are usage patterns that are repeated enough that warrant abstraction - append , len , cap , range are abstractions used to manipulate and query slices. Additionally slicing operations ( a[:1] for example) ","default_branch":null,"files":null,"tree":[],"storefront":"/r/gorgonia","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/gorgonia/tensor/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}