Rocket-Powered Data Science

JULY 19, 2023

This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative. These may not be high risk. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

Cloudera

DECEMBER 3, 2021

Surely there are ways to comb through the data to minimise the risks from spiralling out of control. Systems should be designed with bias, causality and uncertainty in mind. Uncertainty is a measure of our confidence in the predictions made by a system. We need to get to the root of the problem. System Design. Model Drift.

Uncertainty 101

Uncertainty Measurement Metrics Risk 101

O'Reilly on Data

MARCH 31, 2020

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. Underneath this uncertainty lies further uncertainty in the development process itself.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

MARCH 23, 2023

As the world continues to experience economic uncertainty, IT leaders look to tighten budgets, consolidate tools and resources, and generally become more risk-averse when evaluating new investments. Consider your company scorecard: Your procurement team has a scorecard with clear metrics to evaluate purchase decisions.

Scorecard 59

Scorecard Cost-Benefit ROI IT 59

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

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

The Unofficial Google Data Science Blog

AUGUST 27, 2019

Of course, any mistakes by the reviewers would propagate to the accuracy of the metrics, and the metrics calculation should take into account human errors. If we could separate bad videos from good videos perfectly, we could simply calculate the metrics directly without sampling. The missing verdicts create two problems.

Metrics 98

Metrics Statistics Uncertainty Optimization 98