
Show Notes
• Support & get perks! • Proudly sponsored by PyMC Labs! • Intro to Bayes and Advanced Regression courses (first 2 lessons free)
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work ! Chapters: 00:00 The Importance of Decision-Making in Data Science 06:41 From Philosophy to Bayesian Statistics 14:57 The Role of Soft Skills in Data Science 18:19 Understanding Decision Theory Workflows 22:43 Shifting Focus from Accuracy to Business Value 26:23 Leveraging PyTensor for Optimization 34:27 Applying Optimal Decision-Making in Industry 40:06 Understanding Utility Functions in Regulation 41:35 Introduction to Obeisance Decision Theory Workflow 42:33 Exploring Price Elasticity and Demand 45:54 Optimizing Profit through Bayesian Models 51:12 Risk Aversion and Utility Functions 57:18 Advanced Risk Management Techniques 01:01:08 Practical Applications of Bayesian Decision-Making 01:06:54 Future Directions in Bayesian Inference 01:10:16 The Quest for Better Inference Algorithms 01:15:01 Dinner with a Polymath: Herbert Simon
Thank you to my Patrons for making this episode possible! Links from the show: Come meet Alex at the Field of Play Conference in Manchester, UK, March 27, 2026! https://www.fieldofplay.co.uk/ A Bayesian decision theory workflow Daniel's website, LinkedIn and GitHub LBS #124 State Space Models & Structural Time Series, with Jesse Grabowski LBS #123 BART & The Future of Bayesian Tools, with Osvaldo Martin LBS #74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt LBS #76 The Past, Present & Future of Stan, with Bob Carpenter
More from Learning Bayesian Statistics
Support & Resources → Support the show on Patreon → Bayesian Modeling Course (first 2 lessons free)
Today's clip is from Episode 166, featuring Bill Engels & Jesse Grabowski. In this conversation, Bill explains what a kernel means in a Gaussian process and how it defines the idea of similarity between data points. He then breaks down the role of the length scale, showing how it controls how quickly the relationship between two points changes, and how amplitude controls the overall scale of the functions a GP can represent.
Support & Resources → Support the show on Patreon → Bayesian Modeling Course (first 2 lessons free)
Today's clip is from Episode 165, featuring Alex Fengler. In this conversation, Alex introduces Bayesify , a tool that uses AI to analyze research papers and assess how well they follow a Bayesian workflow.
Support & Resources → Support the show on Patreon → Bayesian Modeling Course (first 2 lessons free)