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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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Defining data science in 2018

Data Science and Beyond

I got my first data science job in 2012, the year Harvard Business Review announced data scientist to be the sexiest job of the 21st century. As I was wrapping up my PhD in 2012, I started thinking about my next steps. Things have changed considerably since 2012. What do I actually do here?

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The curse of Dimensionality

Domino Data Lab

The accuracy of any predictive model approaches 100%. Property 4: The accuracy of any predictive model approaches 100%. This means models can always be found that predict group characteristic with high accuracy. There should be no model to accurately predict even and odd rows with random 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 have many routine analyses for which the sparsity pattern is closer to the nested case and lme4 scales very well; however, our prediction models tend to have input data that looks like the simulation on the right.