O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. References.

Modeling 136

Modeling Finance Uncertainty Data mining 136

The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. It is a big picture approach, worthy of your consideration.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

datapine

DECEMBER 28, 2021

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! 3) Data fishing.

Statistics 363

Statistics Advertising Visualization Data mining 363

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

JULY 22, 2020

This post considers a common design for an OCE where a user may be randomly assigned an arm on their first visit during the experiment, with assignment weights referring to the proportion that are randomly assigned to each arm. For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

The result is that experimenters can’t afford to be sloppy about quantifying uncertainty. These typically result in smaller estimation uncertainty and tighter interval estimates. At Google, we tend to refer to them as slices. It has remained an important area of investment for us over the years. A burden has been lifted.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

IBM Big Data Hub

APRIL 10, 2023

In addition to this, network data is generated all the time and everybody has it – indeed, each CSP has an abundant unlimited data source that never stops. Therefore, data mining is the business of every CSP nowadays. We refer here to the ideas, internal gut feelings, etc.

Data mining 60

Data mining Data-driven Uncertainty Data Processing 60