Learning Bayesian Statistics
#3.2 How to use Bayes in industry, with Colin Carroll
Nov 18, 2019
Colin Carroll discusses implementing Bayesian tools in finance and the airline industry, emphasizing effective communication to non-technical stakeholders. He explores challenges in model fitting with golfers' accuracy data, importance of pre-processing features, and practical applications of Bayesian methods. The future of probabilistic programming frameworks is also discussed, along with admiration for Professor Gilbert Strang.
32:06
Episode guests
AI Summary
AI Chapters
Episode notes
Podcast summary created with Snipd AI
Quick takeaways
- Starting with simple models and gradually increasing complexity can prevent pitfalls in industry applications.
- Communicating with visual aids like posterior predictive checks can enhance understanding of complex models for non-technical stakeholders.
Deep dives
Optimizing Models in Industry with Bayesian Tools
Efficiently utilizing Bayesian tools to optimize models in industry is crucial. Implementing patient methods, despite potential time constraints, can be highly beneficial, as seen in applications like modeling risk in the airline industry and pricing coverage for flight tickets. Starting with simple models and iteratively building complexity can prevent pitfalls, such as model failures or slow fittings, highlighting the importance of gradual model development in achieving successful industry applications.
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
