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[PyMCon Webseries] Bayesian Causal Modeling - Q&A 2023-09-28 · 13:00 🎙️ Speaker: Thomas Wiecki \\| ⏰ Time: 1 pm UTC / 6 am PT / 9 am ET / 3 pm Berlin Causal analysis is rapidly gaining popularity, but why? Machine learning methods might help us predict what's going to happen with great accuracy, but what's the value of that if it doesn't tell us what to do to achieve a desirable outcome? Without a causal understanding of the world, it's often impossible to identify which actions lead to a desired outcome. Causal analysis is often embedded in a frequentist framework, which comes with some well-documented baggage. In this talk, Thomas will present how we can super-charge PyMC for Bayesian Causal Analysis by using a powerful new feature: the do operator. Content: 🎥 Async Recorded Talk: https://youtu.be/b47wmTdcICE 📖 Slides: Bayesian Causal Inference 📝 Code: Causal analysis with PyMC: Answering "What If?" with the new do operator 👉 Discourse Post for more details and discussion: https://discourse.pymc.io/t/12912 📢 Note: This session is exclusively for Q&A. We kindly request you to watch the recording before joining the event. For additional information and further discussion, please refer to this Discourse post. 💼 About the Speaker: Thomas Wiecki 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: 👉 Website: www.pymc-labs.com 👉 Twitter: https://twitter.com/twiecki 👉 GitHub: https://github.com/twiecki 🤝 Sponsor We thank our sponsors for supporting PyMC and the PyMCon Web Series. If you would like to sponsor us, contact us for more information. Adia Lab is an independent, Abu Dhabi-based laboratory dedicated to basic and applied research in data and computational sciences. ADIA Lab focuses on societally-important topics such as climate change and energy transition, blockchain technology, financial inclusion and investing, decision making, automation, cybersecurity, health sciences, education, telecommunications, and space, by conducting cutting-edge research in Data Science, Artificial Intelligence, Machine Learning, and High-Performance Computing. 📖 Code of Conduct: Please note that participants are expected to abide by PyMC's Code of Conduct. 🌐 Connecting with PyMC 📺 PyMCon Web Series: https://pymcon.com/ 👥 LinkedIn: https://www.linkedin.com/company/pymc/ 🐦 Twitter: https://twitter.com/pymc_devs 🎥 YouTube: https://www.youtube.com/@pymc-devs 🤝 Meetup: https://www.meetup.com/pymc-online-meetup/ 🐘 Mastodon: https://bayes.club/@pymc 💬 Discourse, Q&A/Discussion: https://discourse.pymc.io 🐙 GitHub: https://github.com/pymc-devs/pymc	[PyMCon Webseries] Bayesian Causal Modeling - Q&A

🎙️ Speaker: Thomas Wiecki \| ⏰ Time: 1 pm UTC / 6 am PT / 9 am ET / 3 pm Berlin

Causal analysis is rapidly gaining popularity, but why? Machine learning methods might help us predict what's going to happen with great accuracy, but what's the value of that if it doesn't tell us what to do to achieve a desirable outcome? Without a causal understanding of the world, it's often impossible to identify which actions lead to a desired outcome.

Causal analysis is often embedded in a frequentist framework, which comes with some well-documented baggage. In this talk, Thomas will present how we can super-charge PyMC for Bayesian Causal Analysis by using a powerful new feature: the do operator.

Content: 🎥 Async Recorded Talk: https://youtu.be/b47wmTdcICE 📖 Slides: Bayesian Causal Inference 📝 Code: Causal analysis with PyMC: Answering "What If?" with the new do operator 👉 Discourse Post for more details and discussion: https://discourse.pymc.io/t/12912

📢 Note: This session is exclusively for Q&A. We kindly request you to watch the recording before joining the event. For additional information and further discussion, please refer to this Discourse post.

💼 About the Speaker:

Thomas Wiecki 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: 👉 Website: www.pymc-labs.com 👉 Twitter: https://twitter.com/twiecki 👉 GitHub: https://github.com/twiecki

🤝 Sponsor We thank our sponsors for supporting PyMC and the PyMCon Web Series. If you would like to sponsor us, contact us for more information.

Adia Lab is an independent, Abu Dhabi-based laboratory dedicated to basic and applied research in data and computational sciences. ADIA Lab focuses on societally-important topics such as climate change and energy transition, blockchain technology, financial inclusion and investing, decision making, automation, cybersecurity, health sciences, education, telecommunications, and space, by conducting cutting-edge research in Data Science, Artificial Intelligence, Machine Learning, and High-Performance Computing.

📖 Code of Conduct: Please note that participants are expected to abide by PyMC's Code of Conduct.

🌐 Connecting with PyMC 📺 PyMCon Web Series: https://pymcon.com/ 👥 LinkedIn: https://www.linkedin.com/company/pymc/ 🐦 Twitter: https://twitter.com/pymc_devs 🎥 YouTube: https://www.youtube.com/@pymc-devs 🤝 Meetup: https://www.meetup.com/pymc-online-meetup/ 🐘 Mastodon: https://bayes.club/@pymc 💬 Discourse, Q&A/Discussion: https://discourse.pymc.io 🐙 GitHub: https://github.com/pymc-devs/pymc

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