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PyMC 3.7 is out, and it features a new way to manage your data within models.
#pymc3 https://medium.com/@pymc_devs/pymc-3-7-making-data-a-first-class-citizen-7ed87fe4bcc5?source=friends_link&sk=2e984396bd3c540bfdafdc8842becf38 … -
#PyMC3 3.6 released! This release comes with new features and bugfixes. The main highlight is our shiny new website https://docs.pymc.io/ courtesy of@colindcarroll. This will also be the last Python 2 compatible release. https://github.com/pymc-devs/pymc3/releases/tag/v3.6 … Update via pip or conda-forge. -
It took 5 years from scratch to publishing. Finally, also the paper about BEAT is published in SRL: https://pubs.geoscienceworld.org/ssa/srl/article-abstract/doi/10.1785/0220190075/580479/The-Bayesian-Earthquake-Analysis-Tool?redirectedFrom=fulltext … Find the code here: https://github.com/hvasbath/beat Powered by
#Pyrocko@team_pyrocko . Cudos also to the great support of the#pymc3 dev-team. -
The
#PyMC3 devs are frequently asked about what's going to happen to the project now that Theano is winding down. Here is a summary of where things are headed. https://medium.com/@pymc_devs/theano-tensorflow-and-the-future-of-pymc-6c9987bb19d5 … -
With
@aloctavodia &@eddericu we're porting to#PyMC3 the end-of-chapter exercises of@rlmcelreath's wonderful book, Statistical Rethinking. There are already 4 chapters online, and more to come
Check it out & give us a hand if you want
https://github.com/pymc-devs/resources/tree/master/Rethinking …Prikaži ovu nit -
Slides for my 2PM talk "The Hamiltonian Monte Carlo Revolution is Open Source - Probabilistic Programming with
#PyMC3" at#ODSCWest https://austinrochford.com/resources/talks/hmc-oss-pymc3-odsc-west-2018.slides.html#/ …pic.twitter.com/zRFhqEFQlp
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Do you have seismic and geodetic (InSAR and GNSS) data, but no code yet to do a joint Bayesian deformation source parameter estimation? Checkout BEAT (Bayesian Earthquake Analysis Tool)! https://hvasbath.github.io/beat/
#pymc3#theano#pyrockopic.twitter.com/PsQurZQf8T
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I've been tracking my steps for several months. Somewhere along the line, I got a puppy. Can Bayesian inference (via
#pymc3) help me identify the day she arrived? http://www.jtash.com/puppy-steps.html …pic.twitter.com/hzRX0x8cvD
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Great (comprehensively updated) post by
@jonsedar on dealing with and detecting outliers in GLMs with#PyMC3 https://sedar.co/posts/glm-robust-regression-using-custom-likelihood-for-outlier-classification/ … -
It's happening! Slowly porting Bayesian delay discounting analysis from Matlab to Python &
#PyMC3. Will also extend to general Delayed and Risky Choice (DARC) tasks. Not ready for use, but taking the scary step of developing in the open https://github.com/drbenvincent/darc-analysis-python …pic.twitter.com/aMAGRvTUj6
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skpro is a supervised
#MachineLearning framework that allows for probabilistic forecasting within a unified interface with the goal to make model assessment and comparison fair, domain-agnostic and approachable. https://github.com/alan-turing-institute/skpro …#PyMC3 integration: https://alan-turing-institute.github.io/skpro/vendors.html#pymc3 … -
Many log CDFs merged into
#PyMC3: https://github.com/pymc-devs/pymc3/pull/2688 … These allow censoring of distributions. Thanks to domenzain for the contribution! -
TIL that volunteering to write docs on something you know nothing about is a great way to learn!
#PyMC3 docs now have more survival analysis stuff
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I just pushed another blogpost in [what is turning out to be] a series about learning how to use
#pymc3. This time: how to learn the off-diagonal elements of the mass matrix. Comments welcome! https://dfm.io/posts/pymc3-mass-matrix/ … -
What
#math happens behind-the-scenes when you hit#PyMC3's Inference Button? I dug in to understand it more deeply. Hint:#gradient#descent doesn't happen here; instead, it's all glued by one equation. https://buff.ly/2rIoJk5#bayesian#bayes#probabilisticprogramming pic.twitter.com/R9jBInHBYe
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I have launched the
#PyDataPodcast! Check out Ep1 with@fonnesbeck where we talk about#ProbabilisticProgramming,#PyMC3,#PyMC4, and baseball analytics http://www.pydata-podcast.com/ It's supposed to be a conversation-based show on more advanced topics, let me know what you think! -
Re-worked my archetypal
#Bayesian data analysis workflow to use#ArviZ - a truly transformational package and a LOT more than pretty Bayesian plots - awesome@arviz_devs https://github.com/AlexIoannides/pymc-example-project …#PYMC3#DataScience#MachineLearning#Statistics -
Great to welcome
@junpenglao who has come to share his#PyMC3 knowledge with our#machinelearning guys in a 2 day workshop on Bayesian statistical modeling. Stay tuned, our Jupyter notebooks and an AV recording of the entire session coming soon.pic.twitter.com/0sa3IYiCYc
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If you're looking for some light Sunday morning reading, I wrote a tutorial for fitting
@NASA_TESS light curves using exoplanet (the code) and#PyMC3: https://exoplanet.dfm.io/en/latest/tutorials/tess/ …Prikaži ovu nit
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