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Podcast: Linear Digressions
Episode:

Empirical Bayes
Category: Technology
Duration: 00:18:57
Publish Date: 2017-02-19 21:30:06
Description: Say you're looking to use some Bayesian methods to estimate parameters of a system. You've got the normalization figured out, and the likelihood, but the prior... what should you use for a prior? Empirical Bayes has an elegant answer: look to your previous experience, and use past measurements as a starting point in your prior. Scratching your head about some of those terms, and why they matter? Lucky for you, you're standing in front of a podcast episode that unpacks all of this.
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