Search Results: Visual Analytics (1744)

Advanced Analytics | Analytics | Artificial Intelligence | Data Management | Students & Educators
Adriana Rojas 0
Por qué los programas en ciencia de datos son un éxito

Hace unas semanas, anunciamos el convenio de colaboración entre el SAS Institute y la Universidad Europea con el objetivo de formar perfiles analíticos gracias a nuestras certificaciones SAS para docencia. En particular, los estudiantes del Doble Grado en Business Analytics + Administración y Dirección de Empresas, así como de los

Analytics | Artificial Intelligence | Data for Good | Data Visualization
Caslee Sims 0
Taking a swing at data literacy: an inside look at The SAS Batting Lab

The SAS Batting Lab is a six-week program designed to help improve kids’ understanding of data while also helping them improve their baseball and softball swings. Using analytics in an interactive, AI-powered batting cage, kids can compare their swings to batting stars. During the program, the participants also became more

Analytics | Artificial Intelligence
Caslee Sims 0
Behind the scenes of the SAS Hackathon: Why being a mentor is a win-win for everyone

During the SAS Hackathon, teams and mentors collaborate to find solutions to specific challenges. The hackathon is a win-win situation for all participants, from idea generation to the development of new technologies or solutions. The SAS Hackathon encourages developers to collaborate on practical ideas and offers employees the chance to

Advanced Analytics | Fraud & Security Intelligence
Aline Riquetti 0
Análise de redes de relacionamento aplicada à prevenção às fraudes e outros crimes financeiros

“Diga-me com quem andas e te direi quem és” é um provérbio popular vastamente conhecido e um consenso entre várias pessoas. Porém, será que essa máxima é verdadeira em todas as situações? Se assim o for, como poderíamos empregar essa relação nas atividades de prevenção a fraude e outros crimes

Analytics | Artificial Intelligence | Internet of Things | SAS Events
Einar Halvorsen 0
Why hack? 10 reasons why the SAS Hackathon is more than a competition

In a hackathon, teams of participants collaborate and compete to find the best solutions to a business or humanitarian challenge using technology. But unlike many traditional hackathons where participants meet in person for a couple of days, the SAS Hackathon is all-digital and lasts for a month. Prior to the

Advanced Analytics | Analytics | Artificial Intelligence
Harry Snart 0
Transforming public sector customer experience with composite AI

Introduction In an era of high connectivity and instant gratification, the expectations of customer experience have never been higher. Customers do not simply want but rather expect accessible and responsive communication across a variety of channels. And for organisations, the risks have never been higher. Disgruntled users now have the

Analytics | Artificial Intelligence | Machine Learning
Andrés Mauricio Torres 0
Procesamiento de Lenguaje Natural, la inteligencia artificial en la era de los metaversos

Recientemente el mundo empezó a hablar con mayor frecuencia de los metaversos, una nueva experiencia en materia de conectividad que llevará a los usuarios a vivir asombrosas experiencias inmersivas y multisensoriales a través de novedosos dispositivos y plataformas tecnológicas. Aún cuando todavía hay muchos interrogantes y alternativas de cómo es

Advanced Analytics | Analytics | Data Visualization
Olivia Ojeda 0
A conversation with Rijkswaterstaat: How SAS is helping keep the Netherlands waterways safe

Rijkswaterstaat (RWS) is the Netherlands main agency for design, construction, management and maintenance for waterways and infrastructure. Their mission is to promote safety, mobility and quality of life in the Netherlands. They are the masterminds behind some of the most prestigious water projects in the world. In a recent panel

Advanced Analytics
Sophia Rowland 0
Generating word embeddings

Word embeddings are the learned representations of words within a set of documents. Each word or term is represented as a real-valued vector within a vector space. Terms or words that reside closer to each other within that vector space are expected to share similar meanings. Thus, embeddings try to capture the meaning of each word or term through its relationships with the other words in the corpus.

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