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Scikit-learn Maintenance and Enhancement for Gradient Boosting

Project scikit-learn

Andreas Mueller (Columbia University)

Funding Cycle 1

Proposal Summary

To improve the open-source machine learning library scikit-learn and aid in maintaining the project, while considering the new implementation of Gradient boosting.



scikit-learn is a Python library for machine learning built on top of SciPy and NumPy and distributed under the 3-Clause BSD license. scikit-learn contains models for supervised and unsupervised learning, as well as tools for preprocessing, model selection and evaluation. It has found wide adoption in research across domains, both in industry and academia, as well as in machine learning applications. It has emerged as one of the go-to solutions for machine learning in the data science community.

Key Personnel

Andreas Mueller
Nicolas Hug