Decision Science with Probabilistic Programming

Explore decision science through probabilistic programming in this 54-minute conference talk from EuroPython 2020. Discover how generative models serve as versatile tools for decision scientists, enabling scenario simulations based on various business hypotheses. Learn how probabilistic programming languages provide inference tools to identify assumptions most likely to generate specific outcomes, facilitating optimal decision-making under uncertainty. Understand the role of generative models in robust optimization and stochastic programming, and see how Python integrates probabilistic programs with these techniques to address high levels of uncertainty in optimization problems. Gain insights into leveraging these powerful methods for more effective business decision-making in uncertain environments.

Mattia Ferrini - Decision Science with Probabilistic Programming