PyData Global 2025

We often must make decisions under uncertainty—should you carry an umbrella if there's a 30 % chance of rain? Bayesian decision theory provides a principled, probabilistic framework to answer such questions by combining beliefs (probabilities), utilities (what matters to us), and actions to maximize expected gain.

This talk:
- Introduces key decision‑theoretic concepts in intuitive terms.
- Uses a toy umbrella example to ground ideas in relatable context.
- Demonstrates applications in Bayesian optimization (PoI/EI) and Bayesian experimental design.
- Is hands‑on—with Python code and practical tools—so participants leave ready to apply these ideas to real‑world problems.