#3.2 How to use Bayes in industry, with Colin Carroll
Learning Bayesian Statistics
Importance of Pre-processing Features and Practical Applications of Bayesian Methods in Industries
This chapter explores the significance of pre-processing features in Bayesian methods, focusing on uncertainty in parameters, impact of priors on model sampling speed, and the role of prior predictive checks. Practical applications of using PYMC3 and probabilistic programming in industries like the online flight industry are discussed, with examples highlighting the importance of thoughtful priors, understanding correlation structures, and analyzing historical data for successful business analysis and decision-making. The chapter also emphasizes the importance of posterior predictive checks, visualization techniques for non-technical audiences, and utilizing parts of the posterior distribution to convey probabilistic thinking in data visualization methods.
