Software Workshop: End-to-End Machine Learning in Model Studio

Effective predictive modeling projects follow the SAS analytics life cycle, from data to discovery and then deployment. SAS Viya provides the capability to perform all these steps from one graphical user interface, making the transition between stages of the analytics life cycle seamless. In this workshop, you load data into memory, prepare input variables for modeling, and build complex analytics pipelines to demonstrate powerful machine learning models. Need to better understand your model? No problem. We’ll show you how to produce model interpretability plots. Need to integrate open-source models? No problem. We’ll show you how to do that and deploy any model with one click. Then the best-performing model is saved and packaged for deployment, and you still have the ability to retrain this model on new data -- all from the same shared interface. Additional resources ◉ Machine Learning Using SAS Viya e-learning – https://support.sas.com/edu/schedules... ◉ SAS Data Mining and Machine Learning Community – https://communities.sas.com/t5/SAS-Da... ◉ SAS Global Certification Program – https://www.sas.com/certify ◉ SAS Learning Subscription – https://www.sas.com/en_us/training/pr... 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