DataRobot

AUGUST 5, 2021

AI and Uncertainty. Some people react to the uncertainty with fear and suspicion. Recently published research addressed the question of “ When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making.”. People are unsure about AI because it’s new. AI you can trust.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. Forecasting at the “push of a button”?

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

Cloudera

DECEMBER 3, 2021

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 understand and provide the greatest human oversight on systems with the greatest levels of uncertainty. System Design. Human Judgement & Oversight. Find out more.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

CIO Business Intelligence

AUGUST 14, 2023

Capitalizing on SAP’s in-memory database, the solution is renowned for meeting the exact challenges Huabao hoped to address navigating uncertainty and refining business results. Rise with SAP S/4HANA Cloud, Private Edition , an ERP tool for large enterprises, would be utilized as the digital core of the new platform.

Key Performance Indicator 98

Key Performance Indicator Sales Manufacturing KPI 98

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. All descriptive statistics can be calculated using quantitative data. Digging into quantitative data. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Jen Stirrup

NOVEMBER 15, 2022

From a data science perspective, it is possible to begin immediately by framing problems regarding machine learning or statistical issues. VUCA stands for volatility, uncertainty, complexity, and ambiguity; these terms could be relevant to many data-based projects. Data strategy in a VUCA environment.

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145

CIO Business Intelligence

NOVEMBER 27, 2023

Cybersecurity risks This one is no surprise, given the scary statistics on the growing number of cyberattacks, the rate of successful attacks, and the increasingly high consequences of being breached. Surveys show a mixed executive outlook, indicating a level of uncertainty about what to expect.

IT 138

IT Digital Transformation Reporting Finance 138

Insight

APRIL 10, 2020

Insight is a community of over 3,000 data scientists, data engineers, machine learning engineers, consensus, DevOps, and security engineers who have completed an Insight Fellows Program and are now members of our professional network. In 2019, over 1,000 Insight Fellows completed one of our 7 programs across 6 locations & remote.

Uncertainty 74

Uncertainty Statistics Machine Learning Publishing 74

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. A machine learning classifier serves this task perfectly. Statistical Science. High Risk 10% 5% 33.3% How Many Strata?

Metrics 98

Metrics Statistics Uncertainty Optimization 98

BI-Survey

MARCH 16, 2021

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. This uncertainty is currently at the forefront of everyone‘s minds. Satisfying customer needs and securing solvency in volatile markets both require quick decisions and decisive action. .

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

MARCH 16, 2021

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. This uncertainty is currently at the forefront of everyone‘s minds. Satisfying customer needs and securing solvency in volatile markets both require quick decisions and decisive action. .

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

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.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43

BI-Survey

FEBRUARY 14, 2022

Overnight, the impact of uncertainty, dynamics and complexity on markets could no longer be ignored. Local events in an increasingly interconnected economy and uncertainties such as the climate crisis will continue to create high volatility and even chaos. The COVID-19 pandemic caught most companies unprepared.

Forecasting 52

Forecasting Uncertainty Measurement Cost-Benefit 52

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. While AGI promises machine autonomy far beyond gen AI, even the most advanced systems still require human expertise to function effectively.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

For example, in our field, we can generally blame machine learning feedback (predictions that change the data itself), budget effects (bidders running out of money in repeated auctions) or even the weather (internet usage changes in complicated ways).

Slice and Dice 46

Slice and Dice Experimentation Data Science Data-driven 46

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. He was saying this doesn’t belong just in statistics. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

JULY 18, 2023

Editor's note : The relationship between reliability and validity are somewhat analogous to that between the notions of statistical uncertainty and representational uncertainty introduced in an earlier post. But for more complicated metrics like xRR, our preference is to bootstrap when measuring uncertainty.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. Hollywood is a $10 billion-a-year industry, and movies range from huge hits to box office bombs.

Risk 67

Risk ROI Modeling Metrics 67

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. Instead of committing to specific outcomes, they commit to a cadence of experimentation, learning, and iteration.

Experimentation 332

Experimentation Testing Metrics Measurement 332