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Structural Evolutions in Data

O'Reilly on Data

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.”

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Using random effects models in prediction problems

The Unofficial Google Data Science Blog

Column "a" is an advertiser id, "b" is a web site, and "c" is the 'interaction' of columns "a" and "b". $y$ We compared the output of a random effects model to a penalized GLM solver with "Elastic Net" regularization (i.e. both L1 and L2 penalties; see [8]) which were tuned for test set accuracy (log likelihood). 1 1 1 1.10