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. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

DECEMBER 4, 2020

NCA doesn’t require the assumption of a specific compartmental model for either drug or metabolite; it is instead assumption-free and therefore easily automated [1]. PharmaceUtical Modeling And Simulation (or PUMAS) is a suite of tools to perform quantitative analytics for pharmaceutical drug development [2]. Mean residence time.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Of particular interest to LSOS data scientists are modeling and prediction techniques which keep improving with more data. Well, it turns out that depending on what it cares to measure, an LSOS might not have enough data. It is certainly true that for any given effect, statistical significance is an SMOD. known, equal variances).

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Ontotext

MAY 18, 2020

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. The capacity and performance of supercomputers is measured with the so-called FLOPS (floating point operations per second). What are supercomputers and why do we need them?

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

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. For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. This renders measures like classification accuracy meaningless. References. The use of multiple measurements in taxonomic problems. Banko, M., & Brill, E. Machine Learning, 57–78.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Posteriors are useful to understand the system, measure accuracy, and make better decisions. But most common machine learning methods don’t give posteriors, and many don’t have explicit probability models. In our model, $theta$ doesn’t depend directly on $x$ — all the information in $x$ is captured in $t$.

KDD 40

KDD Testing Machine Learning Modeling 40