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DOC tidy notebooks (#1535)
* Removed discrete_find_MAP.ipynb Cleanup of several notebooks Additional cleanup of notebooks Cleanup of additional notebooks Removed discrete_find_MAP.ipynb Cleanup of several notebooks Additional cleanup of notebooks Cleanup of additional notebooks WIP: Notebooks updated rugby analytics * Removed discrete_find_MAP.ipynb * Removed discrete_find_MAP.ipynb Cleanup of several notebooks Additional cleanup of notebooks Cleanup of additional notebooks Removed discrete_find_MAP.ipynb Cleanup of several notebooks Additional cleanup of notebooks Cleanup of additional notebooks WIP: Notebooks updated rugby analytics * Cleanup of several notebooks * Additional cleanup of notebooks * Cleanup of additional notebooks * More cleaned up notebooks (including divergent LKJ) * Removed discrete_find_MAP.ipynb Cleanup of several notebooks Additional cleanup of notebooks Cleanup of additional notebooks Removed discrete_find_MAP.ipynb Cleanup of several notebooks Additional cleanup of notebooks Cleanup of additional notebooks WIP: Notebooks updated rugby analytics * Cleanup of several notebooks * More cleaned up notebooks (including divergent LKJ) * DOC Rename pmf example. * DOC Remove glm-logistic as it timeouts on reading data. * DOC Revert LKJ model use Metropolis sampler as NUTS runs into non-singular errors. * DOC Remove NUTS scaling NB as it stops running and is mostly obsolete now that we auto-init in this manner. * DOC Change some samplers in model selection NB to make it faster. * DOC Change getting started guide to use auto-init and auto-assigned samplers. * DOC Remove link to paper as it's out-of-date.
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README.rst

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Getting started
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---------------
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- The `PyMC3
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tutorial <http://pymc-devs.github.io/pymc3/notebooks/getting_started.html>`__ or
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`journal publication <https://peerj.com/articles/cs-55/>`__
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- The `PyMC3 tutorial <http://pymc-devs.github.io/pymc3/notebooks/getting_started.html>`__
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- `PyMC3 examples <http://pymc-devs.github.io/pymc3/examples.html>`__
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and the `API reference <http://pymc-devs.github.io/pymc3/api.html>`__
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- `Probabilistic Programming and Bayesian Methods for Hackers <https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers>`__

docs/source/examples.rst

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.. toctree::
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notebooks/posterior_predictive.ipynb
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notebooks/NUTS_scaling_using_ADVI.ipynb
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notebooks/howto_debugging.ipynb
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notebooks/LKJ.ipynb
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.. toctree::
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notebooks/BEST.ipynb
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notebooks/stochastic_volatility.ipynb
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notebooks/pmf-pymc.ipynb
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notebooks/probabilistic-matrix-factorization.ipynb
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notebooks/rugby_analytics.ipynb
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notebooks/survival_analysis.ipynb
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notebooks/GP-smoothing.ipynb
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notebooks/GLM-robust-with-outlier-detection.ipynb
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notebooks/GLM-model-selection.ipynb
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notebooks/GLM-rolling-regression.ipynb
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notebooks/GLM-logistic.ipynb
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notebooks/GLM-hierarchical.ipynb
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notebooks/GLM-poisson-regression.ipynb
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docs/source/notebooks/Euler-Maruyama and SDEs.ipynb

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docs/source/notebooks/GLM-hierarchical-ADVI.ipynb

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