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Using Empirical Bayes to approximate posteriors for large "black box" estimators

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

These decisions are often business-critical, so it is essential for data scientists to understand and improve the regressions that inform them. In the examples above, we might use our estimates to choose ads, decide whether to show a user images, or figure out which videos to recommend. First, systems can be theoretically intractable.

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Using Empirical Bayes to approximate posteriors for large "black box" estimators

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