Ech hunn pyMC Repeater [1] mol um laafen, mecht schonn e gudden Androck. Et ass wichteg den richtegen Waveshare Lora device ze huelen dann geet et och out of the box m)

Leider nach vill ze roueg an menger Géigend, dofir gesin ech just meng Statistik 😅
[1]https://github.com/rightup/pyMC_Repeater

#meshcore #pyMC #Lëtzebuerg @meshnet #Meshnet_lu

#PyData #Helsinki Talk recordings now up on YouTube:

https://www.youtube.com/@PyData_Helsinki

• #Bayesian analysis of zoo visits with #PyMC and #Marimo notebooks by Teemi Säilynoja
• #LLM evaluation methodology and dashboard in #Python #Plotly by Allan Nevala

本番環境にベイズモデルをデプロイする方法、全部話します
https://qiita.com/Gotoubun_taiwan/items/d543deb6f2b7a2763797?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #Python #R #Stan #PyMC #Numpyro

🚀 New to Variational Inference?

Check out A Beginner’s Guide to VI — a hands-on tutorial from @pymc_labs & @PyData Virginia, led by @fonnesbeck

📺 https://www.youtube.com/watch?v=XECLmgnS6Ng

🎥 Learn VI, ADVI, Pathfinder, & real-world modeling tips from Chris.

#Bayesian #PyMC #ML #MCMC

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

Advancing probabilistic programming for scientific applications?

#EuroSciPy2025 welcomes original research on Bayesian methods, MCMC algorithms, and statistical modeling in #Python.

Submit your work as tutorials, talks, or posters!

#BayesianStatistics #ScientificPython #PyMC #PyStan #EuroSciPy

Developing Bayesian inference methods for complex scientific problems?

#EuroSciPy2025 is seeking original work on Hamiltonian Monte Carlo, variational inference, and statistical modeling in #Python.

Submit your innovations: https://pretalx.com/euroscipy-2025/cfp #CfP

#BayesianStatistics #ScientificPython #BayesianInference #PyMC #PyStan #EuroSciPy

📢 Episode 126 is Live!

🎧 Listen now 👉 https://learnbayesstats.com/episode/126-mmm-clv-bayesian-marketing-analytics-will-dean

🎙️ In this episode with
Alex Andorra, Will Dean from
PyMC-Labs explains how Bayesian methods are reshaping marketing analytics, from MMM to CLV estimation and more ....

#BayesianMarketing #MMM #CLV #MarketingAnalytics #MachineLearning #ProbabilisticProgramming #DataScience #PyMC #Marketing

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

🔴 𝐇𝐨𝐰 𝐓𝐨 𝐅𝐨𝐜𝐮𝐬 𝐎𝐧 𝐖𝐡𝐚𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 𝐈𝐧 𝐓𝐢𝐦𝐞 𝐒𝐞𝐫𝐢𝐞𝐬 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠
🔗 https://learnbayesstats.com/episode/124-state-space-models-structural-time-series-jesse-grabowski

✅ 𝐈𝐧 𝐭𝐡𝐢𝐬 𝐄𝐩𝐢𝐬𝐨𝐝𝐞, 𝐲𝐨𝐮’𝐥𝐥 𝐥𝐞𝐚𝐫𝐧 𝐡𝐨𝐰 𝐭𝐨 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 with @pymc

Alex Andorra & Jesse Grabowski talk about state space models, simplifying forecasting, applications etc.

#LearningBayesianStatistics #PyMC #forecasting #timeseries

I genuinely miss PyMC2. The #PyMC and #Arviz APIs changes so frequently, that it's impossible to know what the standard approach to anything is.

#Bayesian #Statistics in #Python should be easy.

To be honest, I'd really like a well maintained #SkLearn module for it.

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.

#pydata #pydatalondon #pymc #bayesianstats

Cohort Revenue & Retention Analysis with Python 🚀

For those who work with cohort data, I recommend checking Dr.Juan Orduz tutorial for cohort revenue and retention analysis with PyMC 👇🏼

https://www.pymc-labs.com/blog-posts/cohort-revenue-retention/

#python #DataScience #Bayesian #pymc

@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.

It is possible to fit a graphical model with about 10k variables in #pymc or does it just explode? 🙂

So testing some intuition on moving a deterministic analysis into a complex #Bayesian inference problem using #PyMC has been a really fast process. I'm very impressed with how easy it's been to use it. Well chuffed!!!

Did you know that @pymc has a backend enabling live streaming of MCMCs to a #ClickHouse database?

Check out https://github.com/pymc-devs/mcbackend to learn more about #McBackend, and visit https://github.com/pymc-devs/pymc/wiki/GSoC-2024-projects#Extending-McBackend-related-features if you're interested in doing a Google Summer of Code project on this! #PyMC #GSoC #GSoC2024

🚀 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 !

#PyMC #Python #DataScience #Bayesian #OpenSource 🐍📈🎉

Modern #Bayesian samplers like #PyMC are too fast... no way to take a break and having the impression to get things done in parallel... barely the time to toot.

At the encouragement of @nkaretnikov I made a blogpost on how to use #pymc in a more functional style!

https://www.zinkov.com/posts/2023-alternative-frontends-pymc/