CIO Business Intelligence

JUNE 28, 2023

These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As Finally, our goal is to diminish consumer risk evaluation periods by 80% without compromising the safety of our products.” Follow a value-focused strategy.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

The Unofficial Google Data Science Blog

JULY 22, 2020

by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

The Unofficial Google Data Science Blog

AUGUST 27, 2019

But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem. There are many strategies we can use to estimate this quantity, and we will discuss each option in detail. High Risk 10% 5% 33.3%

Metrics 98

Metrics Statistics Uncertainty Optimization 98

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Crucially, it takes into account the uncertainty inherent in our experiments. And sometimes even if it is not[1].)

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

APRIL 17, 2017

Quantification of forecast uncertainty via simulation-based prediction intervals. Such a model risks conflating important aspects, notably the growth trend, with other less critical aspects. In other words, there is an asymmetry of risk-reward when there exists the possibility of misspecifying the weights in $X_C$.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. The AGI would need to handle uncertainty and make decisions with incomplete information. NLP techniques help them parse the nuances of human language, including grammar, syntax and context.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

Domino Data Lab

JUNE 23, 2019

All you need to know, for now, is that machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn based on data by being trained on past examples. I assume a good number of people here have a fair amount of background there.

Management 110

Management Machine Learning Experimentation Metrics 110

O'Reilly on Data

DECEMBER 9, 2019

Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions.

Statistics 33

Statistics Uncertainty Risk Marketing 33

Jet Global

OCTOBER 18, 2021

Factory shutdowns, shipping bottlenecks, and shortages of raw materials have led to substantial uncertainty for businesses seeking to address the vicissitudes of supply-side availability. Statistical demand forecasting may use complex formulas and algorithms to extrapolate future demand based on past history.

Forecasting 52

Forecasting Recreation/Entertainment Sales Finance 52

O'Reilly on Data

APRIL 15, 2025

Use strategic sampling: Rather than evaluating every output, use statistical techniques to sample outputs that provide the most information, particularly focusing on areas where alignment is weakest. This strategy reframes how we think about AI development progress. At any step of the way, if it doesnt work out, we pivot.

Testing 333

Testing Experimentation Metrics Measurement 333

O'Reilly on Data

JUNE 16, 2020

We know, statistically, that doubling down on an 11 is a good (and common) strategy in blackjack. But when making a decision under uncertainty about the future, two things dictate the outcome: (1) the quality of the decision and (2) chance. The decision-making process was fine. We saw this after the 2016 U.S.

Uncertainty 358

Uncertainty Testing Risk Reporting 358