Learn Bayesian regression modeling from the people building #PyMC, #Bambi & #CausalPy.

4 weeks. Live sessions. Real-world use cases.

👉 Registration now open: dub.link/2CDdYLK

#BayesianStatistics #Baysian

Contributing to CausalPy: A Comprehensive Guide for Python Developers Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.

Want to build the future of decision intelligence?

Join #PyMC Labs in contributing to #CausalPy; open-source, Bayesian-powered causal inference for real-world problems.

🚀Watch onboarding: dub.link/3hk7lU0
🧩GitHub: github.com/pymc-labs/Ca...

#CausalInference #OpenSource

Agentic Causal Inference is here! 🙌

By connecting cursor to marimo via MCP, Gemini 3 Pro can execute and iterate on CausalPy models in real-time. From automated sensitivity analysis to Bayesian transparency!

👉Watch: ggl.link/Ifw0lVt

#CausalPy #AgenticAI

In #CausalPy 0.6.0, one of the biggest upgrades isn’t a model, it’s clearer docs, tutorials, and examples + a unique Bayesian lens on structural causal discovery using variable-selection priors in joint models.

🧩Try it on Github: dub.link/Kv99C3L

#BayesianModeling

#CausalPy 0.6.0 drops an enhanced reporting layer:
cleaner tables, consistent summaries, and faster access to “so what?” insights.

A big step toward business-ready Bayesian outputs.
🧩Available on Github: dub.link/yyubQTR

#CausalPy #BayesianModeling

#CausalPy 0.6.0 adds Bayesian Propensity Score Enhancements!

Flexible spline adjustments, improved joint modeling, and an example notebook make scoring more robust, showing how design thinking complements #Bayesian estimation.

🧩Try it on Github: dub.link/9jkcRao

🚀 #CausalPy 0.6.0 is live!

A key highlight: the new Prior class, enabling fully custom #Bayesian priors and advanced setups like spike-and-slab or synthetic control models.

More flexibility, more transparency, better causal modeling.

🧩 𝗖𝗵𝗲𝗰𝗸 𝗶𝘁 𝗼𝘂𝘁 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯: dub.link/QrkzW8C

💥 CausalPy 0.5.0 is out! Now supports multiple treated units in synthetic control — a big boost for geo-lift analysis and more.

📖 Learn more: dub.link/causalpy-v0-...

#CausalPy #CausalInference #PyMC

🚀 CausalPy just hit 1,000+ ⭐ on GitHub — and crossed 120K downloads!

When A/B tests stop, CausalPy starts.

Bayesian. Interpretable. Open-source.

Huge thanks to everyone who’s contributed to the project.
👉Checkout CausalPy: dub.link/causalpy

#CausalPy #PyMCLabs #OpenSource #Bayesian #DataScience

🎄✨ 𝐌𝐞𝐫𝐫𝐲 𝐂𝐡𝐫𝐢𝐬𝐭𝐦𝐚𝐬 𝐚𝐧𝐝 𝐇𝐚𝐩𝐩𝐲 𝐇𝐨𝐥𝐢𝐝𝐚𝐲𝐬 𝐟𝐫𝐨𝐦 𝐏𝐲𝐌𝐂 𝐋𝐚𝐛𝐬!

🎁 This holiday season, we want to thank everyone in our community for your support and enthusiasm. We’re grateful to see so many of you using PyMC-Marketing and CausalPy

#MerryChristmas #HappyNewYear #PyMCMarketing #CausalPy #Gratitude

🎙️ In a recent discussion, @twiecki.bsky.social and Christian Luhmann reflected on their experiences building high-performing remote teams at PyMC Labs, sharing successes, challenges, and lessons learned. Here’s a glimpse:

🔗 youtu.be/AjPfgdS29OY

#Interview #PyMCMarketing #CausalPy