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. After training, the system can make predictions (or deliver other results) based on data it hasn’t seen before. Machine learning adds uncertainty.

Management 332

Management Machine Learning Experimentation Metrics 332

Anmut

OCTOBER 29, 2020

This ongoing trade-off between reporting timely and accurate information strains the reliability of the data. In a time of uncertainty, it also pressures decision-making bodies even more into making the right decision. COVID-19 exposes shortcomings in data management.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

CIO Business Intelligence

JUNE 28, 2022

For example, they may not be easy to apply or simple to comprehend but thanks to bench scientists and mathematicians alike, companies now have a range of logistical frameworks for analyzing data and coming to conclusions. More importantly, we also have statistical models that draw error bars that delineate the limits of our analysis.

Management 136

Management Internet of Things Statistics Data-driven 136

IBM Big Data Hub

SEPTEMBER 28, 2023

Building transparency into IBM-developed AI models To date, many available AI models lack information about data provenance, testing and safety or performance parameters. For many businesses and organizations, this can introduce uncertainties that slow adoption of generative AI, particularly in highly regulated industries.

Testing 92

Testing Finance Enterprise Modeling 92

The Unofficial Google Data Science Blog

APRIL 17, 2017

Quantification of forecast uncertainty via simulation-based prediction intervals. We conclude with an example of our forecasting routine applied to publicly available Turkish Electricity data. They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Occam's Razor

APRIL 8, 2013

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. Remember that the raw number is not the only important part, we would also measure statistical significance. Online, offline or nonline. The result?

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156