Election forecasting: From Bayesian inference to rolling dice by Bernardo Caldas

Bayesian inference is a powerful approach to election forecasting, offering a robust alternative to traditional machine learning techniques when analyzing Portuguese elections. In this talk, Bernardo Caldas explores how probabilistic models handle uncertainty and why Bayesian methods excel when data is scarce. Learn why Bayesian models are particularly effective when data is limited and uncertainty is high - and why, in some cases, rolling dice might be just as valid. Whether you're passionate about politics or simply enjoy probabilistic modeling. This session offers valuable insights and practical applications. :::::: If you love watching content like this, consider joining us in person at the next event: www.datamakersfest.com 👉 FOLLOW US Instagram: https://www.instagram.com/datamakersfest/ LinkedIn: https://www.linkedin.com/showcase/data-makers-fest/ Our channel features talks for anyone building products and services with and around data. Subscribe to our channel for videos on Data Science, Machine Learning, AI, Data Engineering, and more. Data Makers Fest videos may be used for non-commercial purposes under a Creative Commons License, Attribution–Non-Commercial–No Derivatives (or the CC BY – NC – ND 4.0 International). To use the talk for other purposes, please contact us at [email protected]. #datamakersfest #datascience #ai #machinelearning #dataengineering