DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

Risk 111

Risk Modeling IT Risk Management 111

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

The statistics app for Google Sheets hopes to change that. Editor's note: We've mostly portrayed data science as statistical methods and analysis approaches based on big data. Introduction Statistics for Google Sheets is an add-on for Google Sheets that brings elementary statistical analysis tools to spreadsheet users.

Statistics 53

Statistics Big Data Data Science Marketing 53

Smarten

JUNE 17, 2022

It was initiated in 2004 by the Department of Information Technology for implementing the provisions of the 2008 Information Technology Amendment Act. After completion of the testing procedure, the certificate is provided to show that all requirements were met.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

MARCH 27, 2019

Select all rows from the 2008 election. votes_2008 <- filter(presidentialElections, year == 2008). The preceding filter() statement is equivalent to extracting the rows using the following base R syntax: # Select all rows from the 2008 election. votes_2008 <- presidentialElections[presidentialElections$year == 2008, ].

Statistics 85

Statistics Data Science Visualization IT 85

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. 2008 – Financial crisis : scientists flee Wall St.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Since 2008, teams working for our founding team and our customers have delivered 100s of millions of data sets, dashboards, and models with almost no errors. Tie tests to alerts.

Testing 214

Testing Manufacturing Data Quality Statistics 214