2005 and Statistics - Data Leaders Brief

ChatGPT, Author of The Quixote

O'Reilly on Data

MARCH 26, 2024

But perhaps it should infringe something: even when the collection of data is legal (which, statistically, it won’t entirely be for any web-scale corpus), it doesn’t mean it’s legitimate, and it definitely doesn’t mean there was informed consent. To see this, let’s consider another example, that of MegaFace. joined Flickr.

Modeling

Modeling Machine Learning Risk Advertising

Celebrating Women in Data Visualization

Juice Analytics

MARCH 4, 2022

Nightingale was known for her love of statistics. She used her experience in nursing and love of statistics to take data and information that were collected and turn it into charts and graphs like the one below. She worked as a graphics editor from 2005 through 2016 at the NYT.

Visualization

Visualization Statistics Data-driven Interactive

What Are the Most Important Steps to Protect Your Organization’s Data?

Smart Data Collective

APRIL 13, 2021

Based on figures from Statista , the volume of data breaches increased from 2005 to 2008, then dropped in 2009 and rose again in 2010 until it dropped again in 2011. Stolen data can be sold on the black market or used for extortion like in the case of ransomware. The instances of data breaches in the United States are rather interesting.

Testing

Testing Behavioral Analytics Data-driven Big Data

Webinars

How to Achieve High-Accuracy Results When Using LLMs

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Burnout: An IT epidemic in the making

CIO Business Intelligence

NOVEMBER 3, 2023

The stages of burnout Developing over time, burnout builds in distinct stages that lead employees down a path of low motivation, cynicism, and eventually depersonalization, according to Yerbo’s The State of Burnout in Tech report, which points to 2005 research by Salanova and Schaufeli on the subject.

IT

IT Reporting Uncertainty Cost-Benefit

Edmunds sets stage for AI with data infrastructure consolidation

CIO Business Intelligence

JULY 10, 2023

Rokita has been with Edmunds for more than 18 years, starting as executive director of technology in 2005. His role now encompasses responsibility for data engineering, analytics development, and the vehicle inventory and statistics & pricing teams.

Data Warehouse

Data Warehouse Cost-Benefit Unstructured Data Machine Learning

Fitting Bayesian structural time series with the bsts R package

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. They may contain parameters in the statistical sense, but often they simply contain strategically placed 0's and 1's indicating which bits of $alpha_t$ are relevant for a particular computation. by STEVEN L.

Forecasting

Forecasting Statistics Modeling Software

Using random effects models in prediction problems

The Unofficial Google Data Science Blog

MARCH 31, 2016

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. ICML, (2005). [3] Journal of the American Statistical Association 68.341 (1973): 117-130. [5] Journal of the American Statistical Association, Vol. 7] Nicholas A.

Modeling

Modeling Statistics Advertising Testing

New Thinking, Old Thinking and a Fairytale

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. Computerworld – Gartner: Customer-service outsourcing often fails , Scarlet Pruitt, March 2005. Source: Google Trends.

Cost-Benefit

Cost-Benefit Data Warehouse Data Science Consulting

Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

JULY 22, 2016

Or when Tableau and Qlik’s serious entry into the market circa 2004-2005 set in motion a seismic market shift from IT to the business user creating the wave of what was to become the modern BI disruption. After five minutes of seeing these products back then, I just knew they would change everything!

Analytics

Analytics Business Intelligence Metadata Statistics

Data Science, Past & Future

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Tukey did this paper. It’s a great read. It is 50, almost 60 years ago, but he was talking about something that was interdisciplinary.

Data Science

Data Science Machine Learning Data Governance Modeling

Measuring Validity and Reliability of Human Ratings

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. In what follows, assume we have a large number of items and people, so that the measures have little statistical uncertainty.

Measurement

Measurement Metrics Uncertainty Slice and Dice

Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

JULY 1, 2021

statistical model-based techniques – Using Machine Learning we can streamline and simplify the process of building NER models, because this approach does not need a predefined exhaustive set of naming rules. The process of statistical learning can automatically extract said rules from a training dataset. The CRF model.

Modeling

Modeling Statistics Testing Metrics

Rethinking ‘Big Data’ — and the rift between business and data ops

CIO Business Intelligence

MAY 7, 2024

Still, CIOs should not be too quick to consign the technologies and techniques touted during the honeymoon period (circa 2005-2015) of the Big Data Era to the dust bin of history. But many execs suffer from “data defeatism,” erroneously thinking that data value is dependent on having degrees in math, statistics, or machine learning.

Big Data

Big Data Statistics Machine Learning Data Science

Data Leaders Brief

ChatGPT, Author of The Quixote

Celebrating Women in Data Visualization

Webinars

Trending Sources

What Are the Most Important Steps to Protect Your Organization’s Data?

Webinars

Burnout: An IT epidemic in the making

Edmunds sets stage for AI with data infrastructure consolidation

Fitting Bayesian structural time series with the bsts R package

Using random effects models in prediction problems

New Thinking, Old Thinking and a Fairytale

Modernize Using The BI & Analytics Magic Quadrant

Data Science, Past & Future

Measuring Validity and Reliability of Human Ratings

Building a Named Entity Recognition model using a BiLSTM-CRF network

Rethinking ‘Big Data’ — and the rift between business and data ops

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