SAS® Machine Learning

Combining data preparation, feature engineering, modern statistical and machine learning techniques in a single, scalable in-memory processing environment to develop, test and deploy models. SAS Machine Learning on SAS® Analytics Cloud supports the entire machine learning process.

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Key Features of SAS Machine Learning

  • Support for data scientists who prefer accessing SAS® Viya® through a programming interface using either the SAS or Python programming languages.
  • Algorithms that take advantage of ubiquitous parallel computing architectures for fast, accurate results.
  • Advanced optimization techniques to adjust large combinations of hyperparameter settings and return the optimal set automatically for the data scientist.
  • Gradient boosting with automated iterative search for optimal partitioning of data, automated generation of weighted averages and stopping criteria.
  • Factorization machines that apply full pairwise tensor factorization and are enabled for warm restarts to update the model with new transactions without a full retrain.
  • SAS Deep Learning actions, which are cloud-enabled SAS CAS actions released with SAS Viya 3.4. The actions are delivered as part of SAS Machine Learning.
  • Code snippets for quickly inserting SAS code into your program and customizing it to meet your needs. Create your own snippets and add snippets to your list of favorites.
  • Ability to have data scientists with varied programmatic skill sets contribute, taking advantage of existing personnel knowledge with a native interface to Python and the SAS programming language.


Find user's guides and other technical documentation for SAS Machine Learning.

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SAS Machine Learning Blogs & Communities

Connect with other SAS users by joining a users group or attending an upcoming event.

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