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NumPy and Open source

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between NumPy and Open source

NumPy vs. Open source

NumPy (pronounced) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Open source is source code that is made freely available for possible modification and redistribution.

Similarities between NumPy and Open source

NumPy and Open source have 5 things in common (in Unionpedia): Fortran, GitHub, Guido van Rossum, Massachusetts Institute of Technology, Open-source software.

Fortran

Fortran (formerly FORTRAN) is a third generation, compiled, imperative programming language that is especially suited to numeric computation and scientific computing.

Fortran and NumPy · Fortran and Open source · See more »

GitHub

GitHub is a developer platform that allows developers to create, store, manage and share their code.

GitHub and NumPy · GitHub and Open source · See more »

Guido van Rossum

Guido van Rossum (born 31 January 1956) is a Dutch programmer.

Guido van Rossum and NumPy · Guido van Rossum and Open source · See more »

Massachusetts Institute of Technology

The Massachusetts Institute of Technology (MIT) is a private land-grant research university in Cambridge, Massachusetts.

Massachusetts Institute of Technology and NumPy · Massachusetts Institute of Technology and Open source · See more »

Open-source software

Open-source software (OSS) is computer software that is released under a license in which the copyright holder grants users the rights to use, study, change, and distribute the software and its source code to anyone and for any purpose.

NumPy and Open-source software · Open source and Open-source software · See more »

The list above answers the following questions

NumPy and Open source Comparison

NumPy has 82 relations, while Open source has 350. As they have in common 5, the Jaccard index is 1.16% = 5 / (82 + 350).

References

This article shows the relationship between NumPy and Open source. To access each article from which the information was extracted, please visit: