The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Risk and Robustness Our estimates $widehat{beta}$ of the "true'' coefficients $beta$ of our model (1) depend on the random data we observe in experiments, and they are therefore random or uncertain. It is a big picture approach, worthy of your consideration.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Jet Global

OCTOBER 8, 2020

It also decreases the risk of errors by eliminating disjointed, manual processes. A 2017 study by FSN found that businesses which made better use of non-financial data were more than twice as likely to be able to forecast beyond the 12-month time horizon than those that didn’t. Tip 2: Improving accounts receivable procedures.

Finance 98

Finance Reporting Forecasting Uncertainty 98

Cloudera

MAY 15, 2018

My narrower vision of the next advancement in analytics is driven (or biased) by my quantitative risk management background and the critical role that computational simulation capabilities have played in many advances in the world of finance. Derman (2016), Cesa (2017) & Bouchard (2018)). Mauro Cesa. “A Additional resources.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Cloudera

OCTOBER 3, 2018

This communication contains forward-looking statements within the meaning of the federal securities law that are subject to various risks and uncertainties that could cause our actual results to differ materially from those expressed or implied in such statements. Forward-Looking Statements.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

CIO Business Intelligence

FEBRUARY 27, 2023

The IT sector in Ukraine had stabilized after the 2014 Russian incursion with growth accelerating beginning in 2017 and “supercharging” in 2020 and 2021, says Katie Gove, senior director-analyst in Gartner’s Technology and Service Provider Research division. says Koalitionen CEO Amir Mofidi. Aimprosoft felt supported by its customers.

Software 90

Software Marketing Uncertainty Technology 90

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. and an error term ??

Statistics 27

Statistics Uncertainty Risk Marketing 27

CIO Business Intelligence

MARCH 2, 2023

With a talent for developing people and inspiring innovation from her teams, Anita Klopfenstein has built a powerhouse IT organization since joining Little Caesars in 2017 as its CIO. Define the enemy: What are the risks? One of the secrets behind her success as a leader is her love of learning. Define the why: Why are we doing this?

Uncertainty 52

Uncertainty IT Management Testing 52

O'Reilly on Data

SEPTEMBER 11, 2019

So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. 2) is unchanged from Strata NY 2018, it’s up three places from Strata NY 2017—and eight places relative to 2016. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Peter James Thomas

JUNE 20, 2019

© Scott Adams (2017) – dilbert.com. In 2017, a survey estimated that 68 percent of American offices had low or no separation between workers. King was a wise King, but now he was gripped with uncertainty. For example in 20 Risks that Beset Data Programmes. . [7]. And a more competent Chief Risk Officer. .

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

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. 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. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Knowledge Discovery 95

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

Peter James Thomas

AUGUST 12, 2018

A clear parallel would be credit risk in Retail Banking, but something as simple as an estimate of potentially delinquent debtors is an inherently statistical figure (albeit one that may not depend on the output of a statistical model). Ideas for avoiding Big Data failures and for dealing with them if they happen (2017).

Metrics 49

Metrics Statistics Data Quality Measurement 49