Скачать или смотреть #152

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• Proudly sponsored by PyMC Labs! Get in touch at alex.andorra@pymc-labs.com

• Intro to Bayes Course (first 2 lessons free): https://topmate.io/alex_andorra/503302
• Advanced Regression Course (first 2 lessons free): https://topmate.io/alex_andorra/1011122

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !

Takeaways
Decision theory workflows can complement traditional modeling workflows.
Shifting focus from model accuracy to decision value is crucial.
Quantifying the cost of model complexity can guide decision-making.
Optimal decision-making frameworks have vast applications in industry.
Eliciting utility functions can be easier than expected.
Starting simple with decision-making models allows for iterative improvement.
Relating decision-making to financial outcomes resonates with stakeholders.
Uncertainty can significantly impact optimization outcomes.
Risk aversion must be integrated into decision-making frameworks.
Different utility functions can represent varying levels of risk aversion.
Understanding the relationship between utility and belief is key.

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 (https://learnbayesstats.com/#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: https://daniel-saunders-phil.github.i...
Daniel's website: https://daniel-saunders-phil.github.i...
Daniel on LinkedIn:   / dr-daniel-saunders-97239b174  
Daniel on GitHub: https://github.com/daniel-saunders-phil
PreliZ – Exploring and eliciting probability distributions: https://preliz.readthedocs.io/en/latest/
LBS #124 State Space Models & Structural Time Series, with Jesse Grabowski: https://learnbayesstats.com/episode/1...
LBS #123 BART & The Future of Bayesian Tools, with Osvaldo Martin: https://learnbayesstats.com/episode/1...
LBS #74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt: https://learnbayesstats.com/episode/7...
LBS #76 The Past, Present & Future of Stan, with Bob Carpenter: https://learnbayesstats.com/episode/7...