Welcome to another event in the PyMCon Web Series.

To learn about upcoming events check out the website: [ Ссылка ]

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, we will present how we can super-charge PyMC for Bayesian Causal Analysis by using a powerful new feature: the do operator.

Content:
📖 Slides: [ Ссылка ]
📝 Code: [ Ссылка ]

🔗 You can see more details on the Discourse post: [ Ссылка ]
🔗 Register now for the upcoming Q&A session: [ Ссылка ]

About the Speaker:
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: [ Ссылка ]
👉 Twitter: [ Ссылка ]
👉 GitHub: [ Ссылка ]

📢 PyMCon is an asynchronous-first virtual conference for the Bayesian community. Submit your proposal for the PyMCon Web Series CFP and be part of this exciting community. Submit your proposal here: [ Ссылка ]

📧 Join the PyMCon mailing list to stay up-to-date on the latest news, insights, and announcements. 🔗 Join the mailing list here: [ Ссылка ]

🤝 Connect with PyMC
🔗 Website: [ Ссылка ]
🔗 Discourse: [ Ссылка ]
🔗 Meetup: [ Ссылка ]

#PyMConWebSeries #ProbabilisticProgramming #pymc #datascience #ai #machinelearning #programming #datascientist #developer

свернуть