This course shows how to extend the machine learning techniques of SAS Enterprise Miner into an interactive web-based environment. Customized modeling templates will be built to enable sharing of modeling best practices across an organization. You will be able to experiment with Bayesian networks, support vector machines, random forests. and many other machine learning techniques to gain the most insight from your data.

The self-study version of this course contains structured course notes that provide a detailed overview and exercises and that help you develop essential skills. There is also a Virtual Lab that enables you to practice what you learn in the course.

The e-learning includes the following:

• digital course notes for self-study
• Virtual Lab: 30 hours of hands-on software practice

Learn how to stage a modeling tournament to quickly train and validate models on segmented data. Who should attend Predictive modelers, data miners, business analysts, and data scientists Formats available Duration
: 10.5 hours/180 day license

Before attending this course, you should be acquainted with Microsoft Windows and Windows-based software. In addition, you should have at least an introductory-level familiarity with basic statistics and regression modeling, as modeling experience is required. Previous SAS software experience is helpful but not required.

This course addresses SAS Factory Miner software.

A Factory Tour

• motivate the business need for SAS Factory Miner
• discuss the benefits and features of SAS Factory Miner
• navigate through a prebuilt project in SAS Factory Miner

Getting Started - Essentials

• create a project
• access various types of data with Factory Miner

Model Templates and Factory Metadata on Duty

• list available factory templates
• customize a template
• create a new project
• create factory metadata
• run the project with factory metadata

Keeping the Factory Running

• score with SAS Model Manager
• register Factory Miner models
• change user settings

SFMM41