Ontotext

AUGUST 15, 2019

The training is structured to follow the steps of building a simple prototype to test the feasibility of the technology with hands-on guidance by experienced instructors. Still, newcomers are advised to dedicate some time to any of the excellent SPARQL tutorials out there, some of which are referred to in the FAQ section of the training page.

Knowledge Discovery 70

Knowledge Discovery Technology Metadata Interactive 70

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A/B testing is used widely in information technology companies to guide product development and improvements. For questions as disparate as website design and UI, prediction algorithms, or user flows within apps, live traffic tests help developers understand what works well for users and the business, and what doesn’t.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

DECEMBER 4, 2020

Once all packages have been imported, we can move on to loading our test data. We can then proceed with pharmacokinetic modeling, testing the goodness of fit of various models. References. [1] Note that the import may take a while due to the nature of the just-ahead-of-time (JAOT) compiler that Julia uses. Methods Mol Biol.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Ontotext

AUGUST 16, 2019

The training is structured to follow the steps of building a simple prototype to test the feasibility of the technology with hands-on guidance by experienced instructors. Still, newcomers are advised to dedicate some time to any of the excellent SPARQL tutorials out there, some of which are referred to in the FAQ section of the training page.

Knowledge Discovery 40

Knowledge Discovery Technology Metadata Interactive 40

The Unofficial Google Data Science Blog

JANUARY 14, 2016

For this purpose, let’s assume we use a t-test for difference between group means. The statistical effect size is often defined as [ e=frac{delta}{sigma} ]which is the difference in group means as a fraction of the (pooled) standard deviation (sometimes referred to as “Cohen’s d” ). known, equal variances). An effect size of 0.2

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

JULY 22, 2020

This post considers a common design for an OCE where a user may be randomly assigned an arm on their first visit during the experiment, with assignment weights referring to the proportion that are randomly assigned to each arm. There are two common reasons assignment weights may change during an OCE.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Domino Data Lab

MAY 20, 2021

Their tests are performed using C4.5-generated note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). References. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. Chawla et al.,

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136