Remove 2017 Remove Experimentation Remove Statistics Remove Testing
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. And we can keep repeating this approach, relying on intuition and luck. Why experiment with several parameters concurrently?

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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.

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Smarten Advanced Data Discovery is All the Buzz!

Smarten

Advanced Data Discovery allows business users to perform early prototyping and to test hypothesis without the skills of a data scientist, ETL or developer. Advanced Data Discovery ensures data democratization by enabling users to drastically reduce the time and cost of analysis and experimentation.

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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). “ They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Challenges for Transparency ”. Riccardo Guidotti, et al.

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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. It’s by far the most convincing example of a conversation with a machine; it has certainly passed the Turing test. And it can look up an author and make statistical observations about their interests.

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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. We use the diagnostic test results of our regression model to support the reasons why CIs should not be used in financial data analyses. and an error term ??