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Pymc-learn: Practical Probabilistic Machine Learning in Python

Machine Learning 2018-11-05 v1 Machine Learning

Abstract

Pymc-learn\textit{Pymc-learn} is a Python package providing a variety of state-of-the-art probabilistic models for supervised and unsupervised machine learning. It is inspired by scikit-learn\textit{scikit-learn} and focuses on bringing probabilistic machine learning to non-specialists. It uses a general-purpose high-level language that mimics scikit-learn\textit{scikit-learn}. Emphasis is put on ease of use, productivity, flexibility, performance, documentation, and an API consistent with scikit-learn\textit{scikit-learn}. It depends on scikit-learn\textit{scikit-learn} and pymc3\textit{pymc3} and is distributed under the new BSD-3 license, encouraging its use in both academia and industry. Source code, binaries, and documentation are available on http://github.com/pymc-learn/pymc-learn.

Cite

@article{arxiv.1811.00542,
  title  = {Pymc-learn: Practical Probabilistic Machine Learning in Python},
  author = {Daniel Emaasit},
  journal= {arXiv preprint arXiv:1811.00542},
  year   = {2018}
}