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NumPy, a BSD-licensed library that adds support for the manipulation of large, multi-dimensional arrays and matrices; it also includes a large collection of high-level mathematical functions. NumPy serves as the backbone for a number of other numerical libraries, notably SciPy. De facto standard for matrix/tensor operations in Python.
In early 2005, NumPy developer Travis Oliphant wanted to unify the community around a single array package and ported Numarray's features to Numeric, releasing the result as NumPy 1.0 in 2006. [9] This new project was part of SciPy. To avoid installing the large SciPy package just to get an array object, this new package was separated and ...
In computer programming, array slicing is an operation that extracts a subset of elements from an array and packages them as another array, possibly in a different dimension from the original. Common examples of array slicing are extracting a substring from a string of characters, the " ell " in "h ell o", extracting a row or column from a two ...
Release 2.7.9 was released on October 9, 2018 and consists of bug fixes, reorganized code. It is intended to be the last release before IronPython 3. [19] Release 2.7.10 was released on April 27, 2020 and adds .NET Core 3.1 support. [20] Release 2.7.11 was released on November 17, 2020 and resolves issues when running on .NET 5.
In array languages, operations are generalized to apply to both scalars and arrays. Thus, a+b expresses the sum of two scalars if a and b are scalars, or the sum of two arrays if they are arrays. An array language simplifies programming but possibly at a cost known as the abstraction penalty.
[9]: 97 Unlike in NumPy, each data point has an associated label. The collection of these labels is called an index. The collection of these labels is called an index. [ 4 ] : 112 Series can be used arithmetically, as in the statement series_3 = series_1 + series_2 : this will align data points with corresponding index values in series_1 and ...
Learn how to download and install or uninstall the Desktop Gold software and if your computer meets the system requirements.
Google JAX is a machine learning framework for transforming numerical functions. [1] [2] [3] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated Linear Algebra).