The Unofficial Google Data Science Blog

APRIL 23, 2024

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?

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

JULY 22, 2020

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.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

O'Reilly on Data

MARCH 23, 2023

All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. And it can look up an author and make statistical observations about their interests. That’s either the most or the least important question to ask.

IT 348

IT Modeling Testing Risk 348

Smarten

MAY 11, 2017

Advanced Data Discovery ensures data democratization by enabling users to drastically reduce the time and cost of analysis and experimentation. Plug n’ Play Predictive Analysis enables business users to explore power of predictive analytics without indepth understanding of statistics and data science.

Experimentation 49

Experimentation Visualization Predictive Analytics Business Intelligence 49

O'Reilly on Data

DECEMBER 9, 2019

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. and an error term ??

Statistics 32

Statistics Uncertainty Risk Marketing 32

Domino Data Lab

MAY 8, 2019

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.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105