IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. Reactive AI stems from statistical math and can analyze vast amounts of data to produce a seemingly intelligence output.

Machine Learning 73

Machine Learning Deep Learning Interactive Modeling 73

CIO Business Intelligence

JULY 5, 2022

For example, IDC data shows that 2021 there was a boom in monitor sales, with the highest volume of monitors shipped since 2012, at 143.6 million , and this figure is likely due to many professionals giving their home offices a refresh. Additionally, this upgrade can be used as an opportunity to help improve workplace productivity.

Statistics 83

Statistics Sales Visualization Technology 83

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

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

Depict Data Studio

NOVEMBER 4, 2022

I published my first video on November 4, 2012…. ” I’d been a formal statistics tutor and Spanish tutor in college through a small invite-only program. Being a full-time YouTuber is an entirely different business model from being a dataviz speaker and course creator. and the rest was history! My Latest YouTube Stats.

Dashboards 75

Dashboards Testing Software Consulting 75

Domino Data Lab

MARCH 3, 2019

What’s been the impact of using ML models on culture and organization? Who builds their models? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production? “Three surveys of AI adoption reveal key advice from more mature practices”. Management.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

Sisense

DECEMBER 11, 2019

And he explained that the leap to visual-based data discovery put analytics in the hands of data experts working in different lines of business, rather than in IT, where bottlenecks could previously occur, and reporting could take much longer. From a startup in 2012, it is now valued at $3.2 A true unicorn.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

CIO Business Intelligence

FEBRUARY 3, 2023

Much of the work is accomplished by dragging and dropping components in a visual designer, but developers can also adjust the system-generated code in an IDE. Power Advisor tracks statistics about performance to locate bottlenecks and other issues. It offers migration from desktop to a cloud solution, and an open-source edition.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

Domino Data Lab

SEPTEMBER 25, 2019

A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. One of the most common ways of fitting time series models is to use either autoregressive (AR), moving average (MA) or both (ARMA). Chapter Introduction: Time Series and Autocorrelation.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

datapine

MAY 17, 2021

Businesses can benefit from improved data driven decision making as well as enhanced business processes and models and share insights across departments more fluently while propelling intelligent business strategies. What is a discovery model, and how do you use it in a real-world business context? So, what is data discovery?

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161