In this course, you learn to use the R API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook.
You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar R functionality via the SWAT (SAS Wrapper for Analytics Transfer) package.
You then learn to download results to the client and use native R syntax to compare models.
Who should attend:
R users who want to take advantage of SAS Viya distributed analytics for fast and efficient modeling
Before taking this course, you should have experience writing R programs for data analytics.
There are no SAS prerequisites.
This course addresses SAS Viya, SAS Visual Data Mining and Machine Learning software.
Delegates will learn how to
Learn how to:
- Use the R API in SAS Viya.
- Submit CAS actions from R.
- Manage, alter, and prepare data on the CAS server.
- Implement and compare machine learning models on the CAS server.
- Move data between the client and server.
- Use R syntax to wrap up CAS actions with functions and loops.
- Promote data to persist in memory.
SAS Viya and Open Source Integration
- SAS Viya and Cloud Analytic Services (CAS).
- Open source development interfaces.
- Scripting Wrapper for Analytics Transfer (SWAT).
- Fundamentals of the R and Python APIs.
- Predictive modeling.
- Predictive models.
- Model assessment.