O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 258

IT Modeling Testing Risk 258

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Adrian Weller (2017-07-29). “

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Sisense

DECEMBER 3, 2019

Data is the New Oil” was coined by The Economist in May 2017 and became a mantra for organizations to drive new wealth from data. With a single click, an ensemble of univariate forecast models run against your data. An AI algorithm selects the best model based on the type of data analyzed.

Data Warehouse 90

Data Warehouse Analytics Digital Transformation Forecasting 90

datapine

NOVEMBER 27, 2019

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list. Prescriptive analytics goes a step further into the future.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

CIO Business Intelligence

JULY 20, 2022

Yet in the cybersecurity field, women only account for about one quarter (24%) of the overall workforce, albeit, up from 11% in 2017, according to the ISC2 Women in Cybersecurity report. A 2020 World Economic Forum report found that women make up a similar percentage (26%) of data and AI positions in the workforce.

IT 128

IT Software Cost-Benefit Strategy 128

CIO Business Intelligence

FEBRUARY 28, 2023

The startup focused on federal contracts and earned its first contract with the Secret Service in 2017. Digital designer Fearless of Baltimore was awarded the contract to build and maintain the Smithsonian’s first and only digital museum. Today, it employs more than 200.

Metadata 98

Metadata Recreation/Entertainment Cost-Benefit Technology 98

Cloudera

JULY 11, 2021

According to statistics by Singapore’s Ministry of Education, there has been a 3% increase in the number of women pursuing STEM university degrees from 2017 to 2019, as reported by The Straits Times. . Despite companies in the tech industry trying to be more inclusive and diverse, gender diversity still remains an issue.

Sales 103

Sales Consulting Technology Statistics 103

Data Science and Beyond

JANUARY 8, 2017

As of early 2017, fewer than half. My main problem with the Kissmetrics infographic is that it helps feed an illusion of understanding that is prevalent among those with no statistical training. If you only take away one thing from this article, let it be the reminder that it is unwise to blindly accept any formula or model.

Statistics 100

Statistics Modeling Predictive Modeling Marketing 100

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 64

Forecasting Statistics Modeling Software 64

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Sisense

JANUARY 14, 2021

VP of Business Intelligence Michael Hartmann describes the problem: “When an upstream data model change was introduced, it took a few days for us to notice that one of our Sisense charts was ‘broken.’ He co-founded Billie with a group of colleagues in 2017 and now leads the BI team. He works on reporting, analysis, and data modeling.

Dashboards 85

Dashboards Testing Business Intelligence Interactive 85

CIO Business Intelligence

JUNE 14, 2022

Transforming for a Digital Future follows closely in the footsteps of the UK’s previous digital strategy in 2017 that promised to overhaul the civil service, developing skills and culture, using shared platforms, changing back-office processes and systems, and increasing collaboration – focusing in particular on the now soon-to-be retired Gov.UK

Strategy 89

Strategy IT Digital Transformation Data Processing 89

BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. By clubbing various techniques like data mining, machine learning, artificial intelligence and statistical modelling, it makes predictions about events in the future. According to a Federal Bank report, more than $600 billion of household debt in the U.S.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

The Unofficial Google Data Science Blog

JULY 22, 2020

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. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Smarten

NOVEMBER 19, 2018

Predictive analytics employs various analytical and modeling techniques, leveraging historical data and business results to identify crucial relationships, opportunities and risks so that business managers can more accurately predict growth, and competitive and market changes and identify trends and patterns. What is Predictive Analytics?

Business Objectives 40

Business Objectives Predictive Analytics Analytics Forecasting 40

Smarten

JANUARY 3, 2019

Citizen Analysts create and generate data models and use sophisticated analytics that are supported by easy-to-use interactive BI dashboards. By definition, Citizen Analysts are not data scientists, or professional analysts or IT staff. ’ Clearly, Citizen Analysts are here to stay!

Business Intelligence 40

Business Intelligence Statistics Interactive Data Science 40

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. Throughout, we’ll refer to our model-derived measurement of inter-rater reliability as the Intraclass Correlation Coefficient (ICC).

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

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

datapine

NOVEMBER 19, 2019

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience. billion in 2017 to $190.61 Regarding the future growth of AI, it is undeniable.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

AUGUST 8, 2019

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists. The real fun begins once models get deployed in production.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

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

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. This chapter will explore the numbers behind the numbers using ML and then creating an API to serve out the ML model. All of this will be done in the spirit of solving real-world problems in a real-world way. In Figure 6.1,

Statistics 59

Statistics Machine Learning Testing Modeling 59

The Unofficial Google Data Science Blog

APRIL 17, 2017

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. Calendaring was therefore an explicit feature of models within our framework, and we made considerable investment in maintaining detailed regional calendars. Adjustments for effects: holiday, seasonality, and day-of-week effects.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Smarten

NOVEMBER 22, 2017

Self-Serve Advanced Analytics provides a roadmap to guide you through a maze of organizational data with tools and models that will bring together data from disparate sources and enable sophisticated yet simple analytics. These tools allow the enterprise to establish and monitor key metrics and to objectively assess results.

Analytics 40

Analytics IT Business Intelligence Visualization 40

Occam's Razor

JULY 13, 2017

5: What-if Analysis Models. allow for smart elements like modeling. Strategy 5: What-if Analysis Models. Building on the thought above, if you create exploratory environments it can be exceedingly accretive to decision-making if we build in what-if type models. 2: If Complex, Focus! 3: Venn Diagrams FTW! That’s the key.

Visualization 124

Visualization Strategy Interactive Statistics 124

O'Reilly on Data

JANUARY 25, 2021

Our data shows that Chef and Puppet peaked in 2017, when Kubernetes started an almost exponential growth spurt, as Figure 4 shows. Models are neither code nor data, and we don’t have adequate tools for versioning models either (though tools like MLflow are a start). AI, Machine Learning, and Data.

Machine Learning 362

Machine Learning Software Testing Technology 362

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 68

IT Visualization Modeling Uncertainty 68

Domino Data Lab

JANUARY 6, 2019

Also, clearly there’s no “one size fits all” educational model for data science. Laura Noren, who runs the Data Science Community Newsletter , presented her NYU postdoc research at JuptyerCon 2018, comparing infrastructure models for data science in research and education. Wes McKinney (2017). Aurélien Géron (2017).

Data Science 56

Data Science Machine Learning Reporting Visualization 56