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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured. 2018-06-21).

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What Are ChatGPT and Its Friends?

O'Reilly on Data

All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. Tokens ChatGPT’s sense of “context”—the amount of text that it considers when it’s in conversation—is measured in “tokens,” which are also used for billing. Tokens are significant parts of a word.

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The trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics.