What we’re about
PyMC Labs: The Bayesian Consultancy
PyMC is a probabilistic programming library for Python that allows users to fit Bayesian models using a variety of numerical methods, most notably Markov chain Monte Carlo (MCMC) and variational inference (VI). Its flexibility and extensibility make it applicable to a large suite of problems. Along with core model specification and fitting functionality, PyMC integrates with ArviZ for exploratory analysis of the results.
In this Meetup we will discuss topics related to PyMC, statistics, Python, Bayesian Analysis, to name a few.
We also will discuss use cases of PyMC in the business world.
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Contact
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If your company uses PyMC and would like to share about it with our community, please email us: info@pymc-labs.io
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PyMC Labs
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Website: https://www.pymc-labs.io
YouTube: https://www.youtube.com/c/PyMCLabs
LinkedIn: https://www.linkedin.com/company/pymc-labs/
Twitter: https://twitter.com/pymc_labs
PyMC Open Source: https://www.pymc.io/
Upcoming events (1)
See all- [Online] Bayesian VS Causal Modeling: Same, Similar, or Different?Link visible for attendees
🎙️ Speaker: Aleksander Molak, Thomas Wiecki, Carlos Trujillo | ⏰ Time: 14:00 UTC / 7:00 AM PT / 10:00 AM ET / 4:00 PM Berlin
Have you ever wondered about the difference between Bayesian and Causal Modeling? Or how these two approaches can help improve your data analysis? This event is for you!
Join us for an open conversation with our experts, where we’ll explore the key differences, best use cases, and practical tips for using both Bayesian and Causal methods.
What You’ll Learn:
- What makes Bayesian and Causal Modeling different and when to use each.
- Real-life examples and advice from experienced professionals.
- A chance to ask questions and be part of the discussion.
📜 Outline of Talk / Agenda:
- 5 min: Intro to PyMC Labs and speakers
- 45 min: Presentation, panel discussion
- 10 min: Q&A
💼 About the speaker:
- Aleksander Molak (Author of "Causal Inference & Discovery in Python")
Alex is on a mission to make complex ideas simple and easy to understand. He’s an independent machine learning researcher, author, and educator, specializing in causality, NLP, and AI strategy.
🔗 Connect with Alex:
👉 Website: https://alxndr.io/
👉 Youtube: https://www.youtube.com/@CausalPython
👉 Linkedin: https://www.linkedin.com/in/aleksandermolak
👉 Github: https://github.com/alxndrmlk- Carlos Trujillo Agostini (Data Science at PyMC Labs)
Carlos, a seasoned marketing scientist at PyMC Labs, has built a career advancing Marketing Mix Modeling through structured causal models, transforming how data is used in marketing strategies.
🔗 Connect with Carlos:
👉 GitHub: https://github.com/cetagostini
👉 LinkedIn: https://linkedin.com/in/cetagostini💼 About the Host:
- Thomas Wiecki (Founder of PyMC Labs)
Dr. Thomas Wiecki is an author of PyMC, the leading platform for statistical data science. To help businesses solve some of their trickiest data science problems, he assembled a world-class team of Bayesian modelers and founded PyMC Labs -- the Bayesian consultancy. He did his PhD at Brown University studying cognitive neuroscience.
🔗 Connect with Thomas:
👉 Linkedin: https://www.linkedin.com/in/twiecki/
👉 Website: https://www.pymc-labs.com/
https://twiecki.io/
👉 GitHub: https://github.com/twiecki
👉 Twitter: https://twitter.com/twiecki📖 Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.🔗 Connecting with PyMC Labs:
🌐 Website: https://www.pymc-labs.com/
👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/
🐦 Twitter: https://twitter.com/pymc_labs
🎥 YouTube: https://www.youtube.com/c/PyMCLabs
🤝 Meetup: https://www.meetup.com/pymc-labs-online-meetup/
![[Online] Bayesian VS Causal Modeling: Same, Similar, or Different? cover photo](https://secure.meetupstatic.com/photos/event/9/c/6/1/event_524140033.webp "[Online] Bayesian VS Causal Modeling: Same, Similar, or Different?")
