Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Derman (2016), Cesa (2017) & Bouchard (2018)).

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. This post describes the bsts software package, which makes it easy to fit some fairly sophisticated time series models with just a few lines of R code. by STEVEN L. Forecasting (e.g.

Forecasting 66

Forecasting Statistics Modeling Software 66

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

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

The Unofficial Google Data Science Blog

JULY 22, 2020

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. In practice, one may want to use more complex models to make these estimates. For example, one may want to use a model that can pool the epoch estimates with each other via hierarchical modeling (a.k.a.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

The Unofficial Google Data Science Blog

MARCH 13, 2017

Typically, causal inference in data science is framed in probabilistic terms, where there is statistical uncertainty in the outcomes as well as model uncertainty about the true causal mechanism connecting inputs and outputs. We are all familiar with linear and logistic regression models.

IT 70

IT Visualization Modeling Uncertainty 70

IBM Big Data Hub

MARCH 8, 2024

The ecosystem has become more complex as business models advance and new ecommerce trends appear. In recent years, for instance, ecommerce companies based on a subscription model—like Blue Apron and BarkBox— have grown over 1,000%. The ecommerce market has grown exponentially over the last decade.

Consulting 79

Consulting Marketing Sales Data Processing 79

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). A model may for example spit out a figure like £12.4 The model is not saying that £12.4

Statistics 49

Statistics Metrics Data Quality Measurement 49

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 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No. 221) to 2019 (No.

IoT 24

IoT Big Data Data Warehouse Uncertainty 24

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. For example, if a stock has a beta of 1.4

Statistics 31

Statistics Uncertainty Risk Marketing 31

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 97

Software Marketing Uncertainty Technology 97

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