The Unofficial Google Data Science Blog

APRIL 23, 2024

If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). Crucially, it takes into account the uncertainty inherent in our experiments.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

APRIL 17, 2017

For us, demand for forecasts emerged from a determination to better understand business growth and health, more efficiently conduct day-to-day operations, and optimize longer-term resource planning and allocation decisions. Quantification of forecast uncertainty via simulation-based prediction intervals.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Domino Data Lab

JULY 22, 2019

What I’m trying to say is this evolution of system architecture, the hardware driving the software layers, and also, the whole landscape with regard to threats and risks, it changes things. You see these drivers involving risk and cost, but also opportunity. They’re being told they have to embrace uncertainty.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109