This course provides a theoretical foundation for SAS Visual Data Mining and Machine Learning, as well as hands-on experience using the tool through the SAS Visual Analytics interface. The course uses an interactive approach to teach you visualization, model assessment, and model deployment while introducing you to a variety of machine learning techniques.
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual Lab time to practice.
Learn how to
- Train a Bayesian network.
- Train a forest model.
- Train a gradient boosting model.
- Train a neural network.
- Train a support vector machine.
- Train factorization machines.
- Compare models.
- Export model score code and score a model.
- Transfer analytical models from SAS Visual Analytics to Model Studio.
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 in SAS Viya