Machine Learning using SAS Procedures | SAS Viya Workbench Quick Start Tutorial

This tutorial is designed for SAS programmers who want to build and evaluate machine learning models in SAS Viya Workbench using optimized SAS Procedures. You explore basic data preprocessing tasks required for machine learning and then build linear and nonlinear machine learning models to predict a binary target. In addition to best practices, you learn how to compare and evaluate model performance to select a champion model.

Download the data
The SAS Viya Workbench Quick Start Repository provides access to the notebook used in this demonstration – https://github.com/sascommunities/sas...

Chapters
00:00 – Introduction
00:45 – Upload the data
04:53 – Explore the data
06:59 – Partition the data
10:17 – Impute missing values
15:06 – Select useful inputs
19:37 – Logistic regression
23:28 – Decision tree
27:04 – Random forest
29:04 – Gradient Boosting
30:13 – Support Vector Machine
33:03 – Score the models
35:21 – Assess the models
42:53 – Deploy the models
43:38 – Summary

Additional Resources
◉ SAS Viya Workbench – https://www.sas.com/en_us/software/vi...
◉ SAS Viya Workbench Documentation – https://go.documentation.sas.com/doc/...
◉ SAS Learning Subscription – https://www.sas.com/en_us/training/pr...


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