The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. A/B testing is used widely in information technology companies to guide product development and improvements.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

AUGUST 1, 2021

After forming the X and y variables, we split the data into training and test sets. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. 2015) for additional details. For sample 23 from the test set, the model is leaning towards a bad credit prediction.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Posteriors are useful to understand the system, measure accuracy, and make better decisions. Methods like the Poisson bootstrap can help us measure the variability of $t$, but don’t give us posteriors either, particularly since good high-dimensional estimators aren’t unbiased. Figure 4 shows the results of such a test.

KDD 40

KDD Testing Machine Learning Modeling 40