Rocket-Powered Data Science

JULY 19, 2023

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Machine learning adds uncertainty.

Management 339

Management Machine Learning Experimentation Metrics 339

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Occam's Razor

APRIL 8, 2013

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

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., Crucially, it takes into account the uncertainty inherent in our experiments. Here, $X$ is a vector of tuning parameters that control the system's operating characteristics (e.g.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Timo Elliott

JANUARY 18, 2021

And so we scrambled the crisis management team and started looking at the data from very, very early on. It’s very fact-driven, but it’s a combination of facts and how we’re responding as a company and how people are responding personally. And it’s very, very data-driven. It’s a feedback loop.

IT 76

IT Dashboards Digital Transformation Data-driven 76

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. But looking through the blogosphere, some go further and posit that “platformization” of forecasting and “forecasting as a service” can turn anyone into a data scientist at the push of a button.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113