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    Machine learning foundations· 2016

    Probabilistic programming in Python using PyMC3

    John Salvatier (first author) · 2016

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    DOI 10.7717/peerj-cs.55OpenAlex W2217402295

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    Why it matters

    Popularized accessible Bayesian modeling and automated MCMC within Python workflows.

    Condensed from the expert lists' notes.

    The record

    First released
    2016 (from OpenAlex)
    Citations
    2,527 citations, as counted by OpenAlex (CC0)
    Named by
    both expert lists
    Score
    0.307 · computed rank 590 · consensus 0.14, must-read 0, citations percentile 0.757 (2010s · foundations), awards 0, existing lists 0. Method

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.