#pymc — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #pymc, aggregated by home.social.
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PyMC is in Google Summer of Code 2025!
We're excited to be part of #GSoC2025 under @NumFOCUS If you're passionate about #Bayesian stats & #OpenSource, this is your chance to contribute to #PyMC!
📅 Deadline: April 8, 18:00 UTC
🔗 Apply now: https://www.pymc.io/blog/blog_gsoc_2025_announcement.html -
Are you a Python enthusiast looking to explore the power of probabilistic programming? Join us next week at PyHouston to hear Larry Jones introduce #PyMC — the go-to Python library for probabilistic modeling and Bayesian inference!
https://www.meetup.com/python-14/events/305485300/?eventOrigin=group_upcoming_events
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Learning about PyMC makes me want to become a statistician.. super interesting way to think about data, but so much goes into building a good model! So many rabbit holes.
Bayesian modelling is clearly super powerful though and seems to offer some answers to some of the most intractable problems with black-box ML. A reliable model with known and understandable inputs is invaluable for certain use cases.
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@charleemos I have found both the #PyMC tutorials (https://www.pymc.io/projects/docs/en/latest/guides/Gaussian_Processes.html) and the #Stan User's Guide (https://mc-stan.org/docs/stan-users-guide/gaussian-processes.html) on #GaussianProcesses good for getting your hands dirty. Seeing GPs in action and fiddling with hyperparameters was helpful for me to understand the mathematical underpinnings.
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🚀 Introducing "@as_model" in PyMC-Experimental API!
🔥 Key Features:
- Simplifies PyMC modeling
- Better code structure🔗 Details: GitHub PR #268 https://github.com/pymc-devs/pymc-experimental/pull/268
🙌 Thanks to Theo Rashid, @ricardoV94, Rob Zinkov, @twiecki and Maxim Kochurov !
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🚀 Exciting update for #DataScience enthusiasts! Abuzar has pre-recorded a detailed walkthrough on Changepoint Modeling with #PyMC. 📊
🔗 Dive in before the live event for a head-start: https://www.youtube.com/watch?v=iwNju1o5yQo
📓 Grab the notebook: https://github.com/abuzarmahmood/pymcon_bayesian_changepoint/blob/72102ad6149b86d586595bf4523f40f66eb20c25/Bayesian_Changepoint_Zoo_neural_data.ipynb
📅 Join us live for deeper insights and a Q&A session! 👉 https://www.meetup.com/pymc-online-meetup/events/297203071
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🤔 How does our brain turn flavors into data? Uncover the science with Dr. Abuzar Mahmood at #PyMCon.
🎥 Watch the interview: https://www.youtube.com/watch?v=ySF3X45XRyQ
🧠 Get into the nitty-gritty of brain signal analysis using #PyMC.
👉 Details & chat: https://discourse.pymc.io/t/13251 -
📢 Calling all data science enthusiasts and PyMC users!
We're excited to announce the PyMC Docathon on November 17th at 3 PM CET (9 AM ET). This is your chance to contribute to the open-source community and help enhance the PyMC example gallery and documentation.
📆 Save the date: Nov 17, 3pm CET / 14 UTC / 6am PT / 9am ET
🔗 Sign up here: https://www.meetup.com/pymc-online-meetup/events/297172683/
👉 Join the PyMC Discord Server: https://discord.gg/g9vefGNEMH🤝 Lets meet, collaborate, and network with fellow Bayesian enthusiasts. #pymc
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📢 The PyMC community team will be holding office hours to provide an outlet for the community to ask questions, get help, discuss, etc. Office hours are open to everyone, and anyone should feel welcome to attend
📅 Date: Wednesday, 1st Nov, 2023
⏰ Time: 19 UTC / 12 pm PT / 3 pm ET
📍 Where: Online, on Zoom
👉 Register (for Zoom link): https://www.meetup.com/pymc-online-meetup/events/296914851/Office hours will last about an hour, so don't worry if you can't make it at exactly this time! see you there
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🚀 PyMC 5.8.0 is here, packed with some fantastic updates and improvements. 🎉
🆕 New Features:
1️⃣ Causal inference: added the do operator for modeling interventions
2️⃣ Added ICAR distribution
3️⃣ Added JAX implementation for MatrixIsPositiveDefinite Op📒 New example NB 👉 Faster Sampling with JAX and Numba, https://www.pymc.io/projects/examples/en/latest/samplers/fast_sampling_with_jax_and_numba.html
... And many more exciting updates, view the summary of changes here 👉 https://github.com/pymc-devs/pymc/releases/tag/v5.8.0 -
🚀 Just wrapped up an insightful session at PyMCon Web Series! 💡
Missed it? No worries! Here's the recording of Bill Engels' talk on "Introduction to Hilbert Space GPs (HSGPs) in PyMC" 👉 https://www.youtube.com/watch?v=ri5sJAdcYHk
🌟 In this talk, Bill introduced a PyMC Hilbert Space Gaussian Process (HSGP) implementation and showed via case studies how it fills a few key gaps in the PyMC GP library: fast GPs as model subcomponents, and fast GPs with non-Gaussian likelihoods 📊💡.
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📢 The PyMC community team will be holding office hours to provide an outlet for the community to ask questions, get help, discuss, etc. Office hours are open to everyone, and anyone should feel welcome to attend.
📅 Date: Thursday, Sept 14, 2023
⏰ Time: 17 UTC / 10 am PT / 1 pm ET
👉 Register (for Zoom link): www.meetup.com/pymc-online-meetup/events/295908813Office hours will last about an hour, so don't worry if you can't make it at exactly this time! see you there
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Jozsef Arato has translated Chapters 1- 5 of (my + @ShravanVasishth + Daniel Schad) Intro to Bayes for Cog Sci (https://vasishth.github.io/bayescogsci/)
You can find it here:
https://github.com/jozsarato/bayescogdat -
In case you missed the live session on "Automatic Probability - Q&A" by Ricardo Vieira at the PyMCon Web Series, The recording is now available on YouTube.
🎥Recording: https://youtu.be/IdHAST6hgds
Don't miss out on this insightful talk, for more detailed information
🔗 Visit the Discourse post: https://discourse.pymc.io/t/12274
🌐 Explore the official website: https://pymcon.com/events/ -
My first blog post using #bayesian modelling (with #pymc) on estimating tenure effects: https://aurimas.eu/blog/2023/04/modeling-tenure-effects-the-bayesian-way/
I couldn't have done it without going through the fantastic Statistical Rethinking class earlier this year by @rlmcelreath. Highly highly recommend it!
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On Thursday afternoon (15:45) I'll host panel discussion on probabilistic programming (and what does it require to ge a new algorithm added to some PPL package) with panelists
- Mitzi Morris, #Stan / Columbia University
- Junpeng Lao @junpenglao, TFP / #PyMC / Google
- Tor Fjelde, #TuringLang / University of Cambridge
- Henri Pesonen @henri_pesonen, #ELFI / Oslo University Hospital -
📢Calling all #python 🐍 enthusiasts and industry leaders!
Become a sponsor for #PyMCon and help us build the future of Bayesian Modeling. Showcase your brand to a highly engaged community and unlock opportunities for growth and collaboration.
Check out our sponsorship levels and benefits: 👉 http://pymcon.com/sponsors
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Noticias sobre Python científico de la semana, episodio 61 🐍⚙️
En resumen: Versiones nuevas de Ibis y Fugue, análisis bayesiano de retención de cohortes, el futuro de la paquetería en Python, reuniones de PyData en Madrid y Granada, y ChatGPT escribiendo artículos https://astrojuanlu.substack.com/p/episodio-61 Apoya el noticiero suscribiéndote por correo 📫
#noticieropythoncientifico #ibis #fugue #pymc #chatgpt #pydata #python
