Blog, Data Science and KDD - Data Leaders Brief

Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

Recently, we presented some basic insights from our effort to measure and predict long-term effects at KDD 2015 [1]. In this blog post, we summarize that paper and refer you to it for details.

Modeling

Modeling Experimentation Knowledge Discovery KDD

Density-Based Clustering

Domino Data Lab

DECEMBER 2, 2020

In the domain of anomaly detection, this causes problems as anomalous points will be assigned to the same cluster as “normal” data points. In this blog post, I will cover a family of techniques known as density-based clustering. Unlike k-means, DBSCAN does not require the number of clusters as a parameter.

Metrics

Metrics KDD Testing Machine Learning

Using Empirical Bayes to approximate posteriors for large "black box" estimators

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

KDD Testing Machine Learning Measurement

Data Leaders Brief

Experiment design and modeling for long-term studies in ads

Density-Based Clustering

Using Empirical Bayes to approximate posteriors for large "black box" estimators

Webinars

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