The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

MARCH 23, 2021

From 2006: Is Real-Time Analytics Really Relevant? ). In our in-flight optimization journey thus far, we have worked to identify signals that are believable, and identifying at which point they become believable (ex: statistically significant). The benchmark for the beautiful metric AVOC is 15.3%. Here’s an example.

Analytics 131

Analytics Scorecard Strategy Testing 131

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. The problems down in the mature bucket, those are optimizations, they aren’t showstoppers. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JULY 1, 2021

statistical model-based techniques – Using Machine Learning we can streamline and simplify the process of building NER models, because this approach does not need a predefined exhaustive set of naming rules. The process of statistical learning can automatically extract said rules from a training dataset. The CRF model.

Modeling 111

Modeling Statistics Testing Metrics 111