This course introduces SAS Visual Data Mining and Machine Learning for building statistical models in an interactive, exploratory way. Exploratory model fitting is a critical step in modeling big data.

Learn how to

• create a forest model
• create a gradient boosting model
• create a neural network
• create a support vector machine.

Who should attend

Predictive modelers, business analysts, and data scientists who want to take advantage of SAS Visual Data Mining and Machine Learning for highly interactive, rapid model fitting on SAS Viya

Formats available	Duration
Classroom:	7.0 hours
Live Web Classroom:	4 half-day session(s)

Before attending this course, you should

• be acquainted with SAS Visual Statistics
• have at least an introductory-level familiarity with machine learning techniques and statistical modeling.

This course addresses SAS Visual Analytics software.

SAS Visual Data Mining and Machine Learning Overview and Accessing the Data

• introduction

Machine Learning Algorithms

• introduction
• support vector machines
• forests
• gradient boosting
• self-study: useful details

Model Assessment and Implementation

• comparing models and generating score code