NumFOCUS will participate in Google Season of Docs 2019. NumFOCUS promotes open practices in research, data, and scientific computing.
Google Season of Docs is a program to foster open source collaborating with technical writers sponsored by Google. This repository contains information specific to NumFOCUS related organizations participation in GSoD. For general information about the program, including this year's application timeline and key phases involved, please see the GSoD website
This Git repository stores information about NumFOCUS projects applying for Google Season of Docs. All listed projects are applying individually. The repo shows the status for all projects and gives a common place to publish idea lists.
Table of Contents
Welcome, and thank you for taking an interest in NumFOCUS! Read this document to learn how to apply for the GSoD program with NumFOCUS. Please also check out our combined ideas list.
For any questions, please contact the project you want to work with directly.
In alphabetic order.
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MDAnalysis is a Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats |
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NumPy provides an array structure that is *the* fundamental building block of the scientific Python and PyData ecosystems. Website | Ideas List | Contact |
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SciPy is a core package of the scientific Python and PyData ecosystems. It provides a large collection of fundamental algorithms and data structures, from statistics and numerical optimization to linear algebra, Fourier transforms and sparse matrices. Website | Ideas List | Contact |
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The Shogun Machine Learning Toolbox is devoted to making machine learning tools available for free, to everyone. It provides efficient implementation of all standard ML algorithms. Shogun ensures that the underlying algorithms are transparent and accessible—a unified interface provides access via many popular programming languages, including C++, Python, Octave, R, Java, Lua, C#, and Ruby. Website | Ideas List | Contact |