Columbia University

To enable greater use of machine learning techniques in scientific research through technical and user experience improvements to scikit-learn

  • Amount $313,241
  • City New York, NY
  • Investigator Andreas Mueller
  • Year 2017
  • Program Technology
  • Sub-program Data & Computational Research

Written in Python, scikit-learn is an open source machine learning software package used widely across the natural and social sciences (the “software paper” that introduced scikit-learn in 2011 has been cited over 4,700 times). Its maintainers have identified a set of improvements that would make it substantially more efficient for scientific users and enable more reproducible research, but which would require more focused time than any contributor can currently offer. This grant provides funds to Columbia University’s Andreas Mьller, one of the current core maintainers of scikit-learn, to design and implement the identified improvements. These include more flexible data types, better integration with Jupyter notebooks for model exploration, and some technical fixes that will substantially improve platform stability and performance.

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