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🎙️ 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:

1. 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

1. 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:

1. 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/

We talked about:

Aleksander's background Aleksander as a Causal Ambassador Using causality to make decisions Counterfactuals and and Judea Pearl Meta-learners vs classical ML models Average treatment effect Reducing causal bias, the super efficient estimator, and model uplifting Metrics for evaluating a causal model vs a traditional ML model Is the added complexity of a causal model worth implementing? Utilizing LLMs in causal models (text as outcome) Text as treatment and style extraction The viability of A/B tests in causal models Graphical structures and nonparametric identification Aleksander's resource recommendations

Links:

The Book of Why: https://amzn.to/3OZpvBk Causal Inference and Discovery in Python: https://amzn.to/46Pperr Book's GitHub repo: https://github.com/PacktPublishing/Causal-Inference-and-Discovery-in-Python The Battle of Giants: Causality vs NLP (PyData Berlin 2023): https://www.youtube.com/watch?v=Bd1XtGZhnmw New Frontiers in Causal NLP (papers repo): https://bit.ly/3N0TFTL

Free MLOps course: https://github.com/DataTalksClub/mlops-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Unraveling the Secrets of causal Machine Learning - Aleksander Molak

About this event

Outline:

• What is causality in a machine learning sense?
• Causality and LLMs - how causal does ChatGPT think?
• Caveats and pitfalls of causal models
• Causal models in as a product in a business setting

About the guest:

About the speaker:

My name is Aleksander Molak. Friends call me Alex. My mission is to translate complex concepts into understandable bite-size pieces and share them with you. I am an independent machine learning researcher, author, consultant, educator and an entrepreneur. I am specialized in causality, natural language processing (NLP) and AI startegy.

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