TDAN

JUNE 15, 2022

Given that the global big data market is forecast to be valued at $103 billion in 2027, it’s worth noticing. As the amount of data generated […]. “Information is the oil of the 21st century, and analytics is the combustion engine,” says Peter Sondergaard, former Global Head of Research at Gartner. And he has a point.

Data mining 98

Data mining Big Data Forecasting Marketing 98

Domino Data Lab

MAY 20, 2021

In this blog post we talked about why working with imbalanced datasets is typically problematic, and covered the internals of SMOTE – a go-to technique for up-sampling minority classes. Data mining for direct marketing: Problems and solutions. Protein classification with imbalanced data. 30(2–3), 195–215.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

In this blog post, we summarize that paper and refer you to it for details. References [1] Henning Hohnhold, Deirdre O'Brien, Diane Tang, Focus on the Long-Term: It's better for Users and Business , Proceedings 21st Conference on Knowledge Discovery and Data Mining, 2015. [2] 2] Ron Kohavi, Randal M.

Modeling 63

Modeling Experimentation Knowledge Discovery Testing 63

The Unofficial Google Data Science Blog

JULY 22, 2020

Although this blog post makes some specific points about changing assignment weights in an A/B experiment, there is a more general takeaway as well. A/B testing isn’t simple just because data is big — the law of large numbers doesn’t take care of everything! 2] Scott, Steven L. armed bandit experiments in the online service economy."

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Brendan McMahan et al, "Ad Click Prediction: a View from the Trenches" , Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2013. [3] 3] Bradley Efron, "Robbins, Empirical Bayes, and Microarrays" , Technical Report, 2003. [4]

KDD 40

KDD Testing Machine Learning Measurement 40

Domino Data Lab

AUGUST 1, 2021

Conference on Knowledge Discovery and Data Mining, pp. The post Explaining black-box models using attribute importance, PDPs, and LIME appeared first on Data Science Blog by Domino. Guestrin, C., Why should I trust you?: 1135–1144, ACM, 2016. Bahdanau, D., Cho, K., & Bengio, Y.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

The Unofficial Google Data Science Blog

JANUARY 14, 2016

At Google, we have invested heavily in making our estimates of uncertainty evermore accurate (see our blog post on Poisson Bootstrap for an example). The practical consequence of this is that we can’t afford to be sloppy about measuring statistical significance and confidence intervals.

Experimentation 42

Experimentation Statistics Metrics Measurement 42