Ask the Expert Webinar Series

How Do I Get Started With SAS® Visual Data Mining and Machine Learning?

On-Demand • Cost: Complimentary

About the webinar

SAS Visual Data Mining and Machine Learning is designed for the data scientist, statistician and advanced business analyst.

Whether you want to program or point and click, SAS Visual Data Mining and Machine Learning provides innovative algorithms and fast, in-memory processing.

This session covers its capabilities with an accompanying demonstration showing the components of SAS Visual Data Mining and Machine Learning.

You will learn how to:

  • Interactively program in a web-based development environment.
  • Use intelligent automation, including Automatic Feature Engineering node for automatically cleansing, transforming and selecting features for models.
  • Use natural language generation.
  • Incorporate embedded support for Python and R languages.
  • Use highly scalable, distributed in-memory analytical processing.

Sie haben bereits ein SAS Profil? Dieses Formular automatisch ausfüllen: Einloggen

*
*
*
*
 

Ihre persönlichen Daten werden gemäß dem SAS Privacy Statement behandelt.

 
  Ja, ich möchte von SAS Institute Inc. und seinen Tochterunternehmen per E-Mail Informationen zu SAS Produkten, Studien, White Paper und Veranstaltungen erhalten. Mir ist bekannt, dass ich meine Einwilligung jederzeit widerrufen kann, indem ich die Abmeldefunktion in den E-Mails nutze.
Nach dem Absenden dieses Formulars erhalten Sie eine E-Mail, in der wir Sie bitten, Ihre Einwilligung zu bestätigen (Double-Optin-Verfahren). Bitte schauen Sie in Ihrem Posteingang nach einer entsprechenden Nachricht von SAS und klicken den Bestätigungslink. Herzlichen Dank.
 
 

About the Expert


Melodie Rush
Principal Data Scientist
, SAS

Melodie Rush works for the Customer Success Technical Team at SAS. She received both her BS in statistics and her Master of Science in Management from North Carolina State University. Since joining SAS, Rush has developed presentations and methodology for doing many types of analysis, including data mining, forecasting, data exploration and visualization, quality control and marketing. She has spent more than 20 years helping companies identify and solve problems in each of these analytical areas.

 

Back to Top