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Add learn page (#3261)
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‎docs/source/conf.py

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("Quickstart", "intro"),
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("API", "api"),
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("Examples", "examples"),
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("Learn", "learn"),
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],
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# "fixed_sidebar": "false",
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# "description": "Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano"

‎docs/source/index.rst

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Gaussian processes to fit a regression model.</p>
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</div>
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<div class="eight wide right floated column">
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::
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<pre><code class="python">
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X, y = linear_training_data()
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with pm.Model() as linear_model:
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weights = pm.Normal('weights', mu=0, sd=1)
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noise = pm.Gamma('noise', alpha=2, beta=1)
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y_observed = pm.Normal('y_observed',
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mu=X.dot(weights),
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sd=noise,
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observed=y)
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mu=X.dot(weights),
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sd=noise,
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observed=y)
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prior = pm.sample_prior_predictive()
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posterior = pm.sample()
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posterior_pred = pm.sample_posterior_predictive(posterior)
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.. raw:: html
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posterior_pred = pm.sample_posterior_predictive(posterior)</code></pre>
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</div>
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</div>
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</div>
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</div>
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<div class="ui container">
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<h2 class="ui dividing header">etc.</h2>
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<div class="ui text container">
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<h3 class="ui dividing header">License</h3>
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<p>PyMC3 is licensed <a href="https://github.com/pymc-devs/pymc3/blob/master/LICENSE">under the Apache License, V2.</a></p>
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</div>
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<h2 class="ui dividing header">Licence</h2>
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<p>PyMC3 is licensed <a href="https://github.com/pymc-devs/pymc3/blob/master/LICENSE">under the Apache License, V2.</a></p>
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</div>
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<div class="ui text container">
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<h3 class="ui dividing header">Citing PyMC3</h3>
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<p>Salvatier J., Wiecki T.V., Fonnesbeck C. (2016) Probabilistic programming in Python using PyMC3. PeerJ
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Computer Science 2:e55 <a href="https://doi.org/10.7717/peerj-cs.55">DOI: 10.7717/peerj-cs.55</a>.</p>
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<p>See <a href="https://scholar.google.de/scholar?oi=bibs&hl=en&authuser=1&cites=6936955228135731011">Google Scholar</a> for a continuously updated list of papers citing PyMC3.</p>
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</div>
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<div class="ui container">
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<h2 class="ui dividing header">Citing PyMC3</h2>
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<p>Salvatier J., Wiecki T.V., Fonnesbeck C. (2016) Probabilistic programming in Python using PyMC3. PeerJ
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Computer Science 2:e55 <a href="https://doi.org/10.7717/peerj-cs.55">DOI: 10.7717/peerj-cs.55</a>.</p>
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<p>See <a href="https://scholar.google.de/scholar?oi=bibs&hl=en&authuser=1&cites=6936955228135731011">Google Scholar</a> for a continuously updated list of papers citing PyMC3.</p>
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<div class="ui segment">

‎docs/source/learn.rst

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.. title:: Learn
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.. raw:: html
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<h1 class="ui header">Learn Bayesian statistics</h1>
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<h2 class="ui header">...with others!</h2>
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<div class="ui celled list">
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<div class="item">
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<i class="large discourse middle aligned icon"></i>
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<div class="content">
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<a href="https://discourse.pymc.io/" class="header">Discourse Forum</a>
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<div class="description">
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The PyMC3 discourse forum is a great place to ask general questions about Bayesian statistics, or more specific ones about PyMC3 usage.
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</div>
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</div>
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</div>
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<div class="item">
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<i class="large python middle aligned icon"></i>
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<div class="content">
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<div class="header">Conferences</div>
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<div class="description">
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PyMC3 talks have been given at a number of conferences, including <a href="https://us.pycon.org/">PyCon</a>, <a href="https://pydata.org/events/">PyData</a>, and <a href="https://odsc.com/">ODSC</a> events.
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</div>
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</div>
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</div>
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<div class="item">
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<i class="large meetup middle aligned icon"></i>
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<div class="content">
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<a href="https://www.meetup.com/" class="header">Meetup Groups</a>
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<div class="description">
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Many areas have an local Bayesian, PyData, or Stan meetup.
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</div>
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</div>
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</div>
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</div>
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<h2 class="ui header">...with a book!</h2>
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<div class="ui link four stackable cards">
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<div class="card">
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<div class="image">
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<img src="https://camo.githubusercontent.com/4a0aca82ca82efab71747d00db30f3a68de98e82/687474703a2f2f692e696d6775722e636f6d2f36444b596250622e706e673f31">
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</div>
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<div class="content">
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<div class="header">Bayesian Methods for Hackers</div>
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<div class="meta">Cameron Davidson-Pilon</div>
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<div class="description">
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Fantastic book with many applied code examples.
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</div>
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</div>
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<table class="ui table">
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<tbody>
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<tr>
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<td>
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<a href="https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers">
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<i class="linkify icon"></i> Github Repo
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</a>
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</td>
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</tr>
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<tr>
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<td>
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<a href="http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/">
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<i class="linkify icon"></i> Project homepage
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</a>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<div class="card">
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<div class="image">
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<img src="https://camo.githubusercontent.com/dbb5f926b3bfe7e2196044462ce2411ee3a001ee/68747470733a2f2f39623865303033322d612d36326362336131612d732d73697465732e676f6f676c6567726f7570732e636f6d2f736974652f646f696e67626179657369616e64617461616e616c797369732f776861742d732d6e65772d696e2d326e642d65642f436f7665724442444132452d46726f6e744f6e6c792d363030776964652e706e67">
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</div>
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<div class="content">
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<div class="header">Doing Bayesian Data Analysis</div>
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<div class="meta">John Kruschke</div>
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<div class="description">
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Principled introduction to Bayesian data analysis.
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</div>
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</div>
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<table class="ui table">
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<tbody>
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<tr>
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<td>
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<a href="http://doingbayesiandataanalysis.blogspot.com/">
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<i class="linkify icon"></i> Book website
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</a>
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<a href="https://github.com/aloctavodia/Doing_bayesian_data_analysis">
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<i class="linkify icon"></i> PyMC3 notebooks for <em>first edition</em>
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</a>
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</td>
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</tr>
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<a href="https://github.com/JWarmenhoven/DBDA-python">
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<i class="linkify icon"></i> PyMC3 notebooks for <em>second edition</em>
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</a>
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</tbody>
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</table>
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</div>
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<div class="card">
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<div class="image">
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<img src="http://xcelab.net/rm/wp-content/uploads/2012/01/9781482253443-191x300.jpg">
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</div>
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<div class="content">
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<div class="header">Statistical Rethinking</div>
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<div class="meta">Richard McElreath</div>
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<div class="description">
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A Bayesian Course with Examples in R and Stan.
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</div>
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</div>
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<a href="http://xcelab.net/rm/statistical-rethinking/">
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<i class="linkify icon"></i> Book website
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<a href="https://github.com/pymc-devs/resources/tree/master/Rethinking">
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<i class="linkify icon"></i> PyMC3 port of the code
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</a>
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</tbody>
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</table>
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</div>
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<div class="card">
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<div class="image">
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<img src="https://images-na.ssl-images-amazon.com/images/I/51K33XI2I8L._SX330_BO1,204,203,200_.jpg">
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</div>
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<div class="content">
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<div class="header">Bayesian Cognitive Modeling: A Practical Course</div>
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<div class="meta">Michael Lee and Eric-Jan Wagenmakers</div>
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<div class="description">
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Focused on using Bayesian statistics in cognitive modeling.
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</div>
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</div>
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<table class="ui table">
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<a href="https://bayesmodels.com/">
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<i class="linkify icon"></i> Book website
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</a>
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<a href="https://github.com/pymc-devs/resources/tree/master/BCM">
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<i class="linkify icon"></i> PyMC3 implementations
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</a>
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</tbody>
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</table>
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</div>
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<div class="card">
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<div class="image">
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<img src="https://dz13w8afd47il.cloudfront.net/sites/default/files/imagecache/ppv4_main_book_cover/3804OS_4958_Bayesian%20Analysis%20with%20Python.png">
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</div>
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<div class="content">
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<div class="header">Bayesian Analysis with Python</div>
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<div class="meta">Osvaldo Martin</div>
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A great introductory book written by a maintainer of PyMC3.
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<a href="https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python">
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<i class="linkify icon"></i> Book website
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<a href="https://github.com/aloctavodia/BAP">
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<i class="linkify icon"></i> Code and errata in PyMC3
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</a>
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</tbody>
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</table>
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</div>
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<div class="card">
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<img src="http://www.stat.columbia.edu/~gelman/book/bda_cover.png">
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<div class="content">
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<div class="header">Bayesian Data Analysis</div>
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<div class="meta">Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin</div>
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<div class="description">
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A comprehensive, standard, and wonderful textbook on Bayesian methods.
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</div>
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<table class="ui table">
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<a href="https://www.stat.columbia.edu/~gelman/book/">
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<i class="linkify icon"></i> Book website
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<a href="https://github.com/pymc-devs/resources/tree/master/BDA3">
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<i class="linkify icon"></i> Examples and exercises implemented in PyMC3
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</a>
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</div>
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<h2 class="ui header">...with a video!</h2>
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<p> There is an <a href="https://www.youtube.com/playlist?list=PL1Ma_1DBbE82OVW8Fz_6Ts1oOeyOAiovy">actively curated playlist of PyMC3 talks</a> on YouTube.

‎docs/source/semantic_sphinx/layout.html

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<div class="ui container">
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{% if theme_navbar_links %}
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<a href="{{ pathto(*link[1:]) }}" class="item">{{ link[0] }}</a>
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<img class="ui bottom aligned tiny image item" src="https://cdn.rawgit.com/pymc-devs/pymc3/master/docs/logos/svg/PyMC3_banner.svg" />
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{% if
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theme_navbar_links %} {%- for link in theme_navbar_links %} <a href="{{ pathto(*link[1:]) }}" class="item">{{
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{% endif %}
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<div class="right menu">

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