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. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 332

Management Machine Learning Experimentation Metrics 332

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. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 93

Testing Finance Enterprise Modeling 93

CIO Business Intelligence

AUGUST 14, 2023

The collaboration between Huabao and SAP continued as plans for a new foundation to support corporate development and business model transformation gathered speed. 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.

Key Performance Indicator 96

Key Performance Indicator Sales Manufacturing KPI 96

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 Belcorp operates under a direct sales model in 14 countries. Its brands include ésika, L’Bel, and Cyzone, and its products range from skincare and makeup to fragrances.

Digital Transformation 92

Digital Transformation Cost-Benefit Informatics Data mining 92

CIO Business Intelligence

NOVEMBER 3, 2023

This overall lack of engagement leads to a sense of detachment, increasing the risk that many in your department may quit or completely check-out in their role. Women disproportionately affected by burnout For women, the statistics around burnout are even worse.

IT 131

IT Reporting Uncertainty Cost-Benefit 131

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. 75 percent of companies confirm that predictive models provide good forecasts for them, even in volatile markets.

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. 75 percent of companies confirm that predictive models provide good forecasts for them, even in volatile markets.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

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

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Cloudera

MARCH 2, 2018

Banking, transportation, healthcare, retail, and real estate, all have seen the emergence of new business models fundamentally changing how customers use their services. Identify those most at risk or most affected by a problem more accurately by using predictive analytics. The model integrates and analyses hundreds of data elements.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42

The Unofficial Google Data Science Blog

APRIL 17, 2017

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. Quantification of forecast uncertainty via simulation-based prediction intervals. Calendaring was therefore an explicit feature of models within our framework, and we made considerable investment in maintaining detailed regional calendars.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

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

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. High Risk 10% 5% 33.3% Statistical Science. Statistics in Biopharmaceutical Research, 2010. [4] How Many Strata?

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Peter James Thomas

AUGUST 12, 2018

Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7]. The thing with statistical estimates is that they are never a single figure but a range. million ± £0.5

Metrics 49

Metrics Statistics Data Quality Measurement 49

Domino Data Lab

JULY 22, 2019

how “the business executives who are seeing the value of data science and being model-informed, they are the ones who are doubling down on their bets now, and they’re investing a lot more money.” He was saying this doesn’t belong just in statistics. Key highlights from the session include. Transcript. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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. When we shipped an algorithm update, when we improved the model, you would see a step function change in that growth.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

MAY 31, 2016

Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. This is a quantity that is easily interpretable and summarizes nicely the statistical power of the experiment.

Advertising 42

Advertising Testing Sales Statistics 42

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment.

Statistics 27

Statistics Uncertainty Risk Marketing 27

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

CIO Business Intelligence

FEBRUARY 12, 2024

4 Additionally, while 63% have guardrails in place to use AI safely, these organizations worry about its role in misinformation, ethical bias and job loss among other risks, Wavestone found. High-quality data will be the oil that makes your models hum. Some of this will hinge on what you want your model to do.

IT 122

IT Consulting Cost-Benefit Uncertainty 122

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