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Commit 2f3987e

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EmaasitEmaasit
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Merge pull request #16 from Emaasit/docs
updated docs with arxiv reference and pymc4 note
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‎CONTRIBUTING.rst

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- Lines should be a maximum of 80 characters long
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- Docstrings should be written as numpy docstrings
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- Your code should be Python 3 compatible
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- When in doubt, follow the style of the existing code
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- When in doubt, follow the style of the existing code
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Transitioning from PyMC3 to PyMC4
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-----------------------------------
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.. raw:: html
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<embed>
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<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">.<a href="https://twitter.com/pymc_learn?ref_src=twsrc%5Etfw">@pymc_learn</a> has been following closely the development of <a href="https://twitter.com/hashtag/PyMC4?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC4</a> with the aim of switching its backend from <a href="https://twitter.com/hashtag/PyMC3?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC3</a> to PyMC4 as the latter grows to maturity. Core devs are invited. Here&#39;s the tentative roadmap for PyMC4: <a href="https://t.co/Kwjkykqzup">https://t.co/Kwjkykqzup</a> cc <a href="https://twitter.com/pymc_devs?ref_src=twsrc%5Etfw">@pymc_devs</a> <a href="https://t.co/Ze0tyPsIGH">https://t.co/Ze0tyPsIGH</a></p>&mdash; pymc-learn (@pymc_learn) <a href="https://twitter.com/pymc_learn/status/1059474316801249280?ref_src=twsrc%5Etfw">November 5, 2018</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
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</embed>

‎README.rst

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``pymc-learn`` leverages and extends the Base template provided by the
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PyMC3 Models project: https://github.com/parsing-science/pymc3_models
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Transitioning from PyMC3 to PyMC4
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..................................
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.. raw:: html
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<embed>
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<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">.<a href="https://twitter.com/pymc_learn?ref_src=twsrc%5Etfw">@pymc_learn</a> has been following closely the development of <a href="https://twitter.com/hashtag/PyMC4?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC4</a> with the aim of switching its backend from <a href="https://twitter.com/hashtag/PyMC3?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC3</a> to PyMC4 as the latter grows to maturity. Core devs are invited. Here&#39;s the tentative roadmap for PyMC4: <a href="https://t.co/Kwjkykqzup">https://t.co/Kwjkykqzup</a> cc <a href="https://twitter.com/pymc_devs?ref_src=twsrc%5Etfw">@pymc_devs</a> <a href="https://t.co/Ze0tyPsIGH">https://t.co/Ze0tyPsIGH</a></p>&mdash; pymc-learn (@pymc_learn) <a href="https://twitter.com/pymc_learn/status/1059474316801249280?ref_src=twsrc%5Etfw">November 5, 2018</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
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</embed>
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Familiar user interface
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To cite ``pymc-learn`` in publications, please use the following::
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Emaasit, Daniel (2018). Pymc-learn: Practical probabilistic machine
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learning in Python. arXiv preprint arXiv:1810.xxxxx.
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learning in Python. arXiv preprint arXiv:1811.00542.
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Or using BibTex as follows:
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@article{emaasit2018pymc,
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title={Pymc-learn: Practical probabilistic machine learning in {P}ython},
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author={Emaasit, Daniel and others},
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journal={arXiv preprint arXiv:1810.xxxxx},
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journal={arXiv preprint arXiv:1811.00542},
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year={2018}
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}
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‎docs/cite.rst

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To cite ``pymc-learn`` in publications, please use the following::
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Pymc-learn Developers Team (2019). pymc-learn: Practical probabilistic machine
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learning in Python. arXiv preprint arXiv:xxxx.xxxxx. Forthcoming.
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Emaasit, Daniel (2018). Pymc-learn: Practical probabilistic machine
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learning in Python. arXiv preprint arXiv:1811.00542.
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Or using BibTex as follows:
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.. code-block:: latex
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@article{Pymc-learn,
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title={pymc-learn: Practical probabilistic machine learning in {P}ython},
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author={Pymc-learn Developers Team},
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journal={arXiv preprint arXiv:xxxx.xxxxx},
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year={2019}
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@article{emaasit2018pymc,
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title={Pymc-learn: Practical probabilistic machine learning in {P}ython},
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author={Emaasit, Daniel and others},
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journal={arXiv preprint arXiv:1811.00542},
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year={2018}
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}
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If you want to cite ``pymc-learn`` for its API, you may also want to consider

‎docs/develop.rst

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To report an issue with ``pymc-learn`` please use the `issue tracker <https://github.com/pymc-learn/pymc-learn/issues>`__.
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Finally, if you need to get in touch for information about the project, `send us an e-mail <devs@pymc-learn.org>`__.
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Transitioning from PyMC3 to PyMC4
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-----------------------------------
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.. raw:: html
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<embed>
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<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">.<a href="https://twitter.com/pymc_learn?ref_src=twsrc%5Etfw">@pymc_learn</a> has been following closely the development of <a href="https://twitter.com/hashtag/PyMC4?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC4</a> with the aim of switching its backend from <a href="https://twitter.com/hashtag/PyMC3?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC3</a> to PyMC4 as the latter grows to maturity. Core devs are invited. Here&#39;s the tentative roadmap for PyMC4: <a href="https://t.co/Kwjkykqzup">https://t.co/Kwjkykqzup</a> cc <a href="https://twitter.com/pymc_devs?ref_src=twsrc%5Etfw">@pymc_devs</a> <a href="https://t.co/Ze0tyPsIGH">https://t.co/Ze0tyPsIGH</a></p>&mdash; pymc-learn (@pymc_learn) <a href="https://twitter.com/pymc_learn/status/1059474316801249280?ref_src=twsrc%5Etfw">November 5, 2018</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
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‎docs/install.rst

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It is recommend installing Python and key numerical libraries using the `Anaconda Distribution <https://www.continuum.io/downloads>`_,
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which has one-click installers available on all major platforms.
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Assuming a standard Python environment is installed on your machine (including pip), ``pymc-learn`` itself can be installed in one line using pip:
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Assuming a standard Python environment is installed on your machine
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(including pip), ``pymc-learn`` itself can be installed in one line using pip:
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.. code-block:: python
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You can install ``pymc-learn`` from PyPi using pip as follows:
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pip install pymc-learn
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Or from source as follows:
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pip install git+https://github.com/pymc-learn/pymc-learn
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.. CAUTION::
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``pymc-learn`` is under heavy development.
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pip install git+https://github.com/pymc-learn/pymc-learn
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This also installs required dependencies including Theano.
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For alternative Theano installations (e.g., gpu), please see the
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instructions on the main `Theano webpage <http://deeplearning.net/software/theano/>`_.
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Transitioning from PyMC3 to PyMC4
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.. raw:: html
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<embed>
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<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">.<a href="https://twitter.com/pymc_learn?ref_src=twsrc%5Etfw">@pymc_learn</a> has been following closely the development of <a href="https://twitter.com/hashtag/PyMC4?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC4</a> with the aim of switching its backend from <a href="https://twitter.com/hashtag/PyMC3?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC3</a> to PyMC4 as the latter grows to maturity. Core devs are invited. Here&#39;s the tentative roadmap for PyMC4: <a href="https://t.co/Kwjkykqzup">https://t.co/Kwjkykqzup</a> cc <a href="https://twitter.com/pymc_devs?ref_src=twsrc%5Etfw">@pymc_devs</a> <a href="https://t.co/Ze0tyPsIGH">https://t.co/Ze0tyPsIGH</a></p>&mdash; pymc-learn (@pymc_learn) <a href="https://twitter.com/pymc_learn/status/1059474316801249280?ref_src=twsrc%5Etfw">November 5, 2018</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
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‎docs/why.rst

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The underlying probabilistic models are built using pymc3 (Salvatier et al., 2016).
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<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">.<a href="https://twitter.com/pymc_learn?ref_src=twsrc%5Etfw">@pymc_learn</a> has been following closely the development of <a href="https://twitter.com/hashtag/PyMC4?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC4</a> with the aim of switching its backend from <a href="https://twitter.com/hashtag/PyMC3?src=hash&amp;ref_src=twsrc%5Etfw">#PyMC3</a> to PyMC4 as the latter grows to maturity. Core devs are invited. Here&#39;s the tentative roadmap for PyMC4: <a href="https://t.co/Kwjkykqzup">https://t.co/Kwjkykqzup</a> cc <a href="https://twitter.com/pymc_devs?ref_src=twsrc%5Etfw">@pymc_devs</a> <a href="https://t.co/Ze0tyPsIGH">https://t.co/Ze0tyPsIGH</a></p>&mdash; pymc-learn (@pymc_learn) <a href="https://twitter.com/pymc_learn/status/1059474316801249280?ref_src=twsrc%5Etfw">November 5, 2018</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
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Python is the lingua franca of Data Science
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--------------------------------------------
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References
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...........
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------------
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1. Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452.
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