SAS Users
Providing technical tips and support information, written for and by SAS users.
Managing workloads in modern analytics environments is not keeping systems running, it’s about making sure the right jobs get the right resources at the right time. As organizations move analytics to the cloud, powered by Kubernetes, balancing workloads across computer resources becomes a critical challenge.
Learn how to seamlessly register and deploy Python models (specifically an XGBoost classifier) into SAS Model Manager using SAS Viya Workbench and the pzmm package, enabling efficient ModelOps integration and production readiness.
Let SAS handle the data prep, R take care of the modeling, and skip the environment-hopping so your team can focus on building cool stuff faster.
Learn how to modernize legacy SAS workflows by integrating Python and automating processes using GitHub Actions and SAS Viya Workbench, enabling seamless collaboration and CI/CD across development environments.
Hyperparameter autotuning intelligently optimizes machine learning model performance by automatically testing parameter combinations, balancing accuracy and generalizability, as demonstrated in a real-world particle physics use case.
A hands-on introduction to SAS Notebooks in SAS Viya Workbench, showing how to combine code, SQL, and Markdown for a more productive and interactive coding experience.