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In this video, Wendy Czika of SAS demonstrates how to use the SAS Code node when executing SAS code in SAS Visual Data Mining and Machine Learning pipelines, as part of the Model Studio application. The SAS Visual Data Mining and Machine Learning pipeline provides an easy-to-use, interactive environment to not only build complex machine learning models but also a nice way to visualize the process and create re-usable pipelines. Wendy Czika is a senior manager who is part of the Advanced Analytics division at SAS. Content Outline 00:10 – What is the SAS Visual Data Mining and Machine Learning pipeline? 01:39 – How can I add custom code to the pipeline? The SAS Code node! 02:42 – What are common use cases of the SAS Code node? 03:02 – How can I use the SAS Code node for preprocessing? 05:25 – How can I use the SAS Code node for data summarization and visualization? 05:58 – SAS Code node demo in Model Studio 13:19 – Where can I find more information? Related Resources ◉ GitHub has lots of great examples, with more coming every day! – https://github.com/sassoftware/sas-vi... ◉ SAS Data Mining and Machine Learning Community – https://communities.sas.com/t5/SAS-Co... ◉ SAS Code node documentation – https://go.documentation.sas.com SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS https://www.youtube.com/SASUsers?sub_... ABOUT SAS SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change. CONNECT WITH SAS SAS ► https://www.sas.com SAS Customer Support ► https://support.sas.com SAS Communities ► https://communities.sas.com SAS Analytics Explorers ► https://explorers.sas.com Facebook ► / sassoftware Twitter ► / sassoftware LinkedIn ► / sas Blogs ► https://blogs.sas.com RSS ► https://www.sas.com/rss