Intermediate

Discovering and Predicting Patterns Using Neural Network Models

Application Area:
Statistics, Predictive Modeling, and Data Mining

See how to use JMP and JMP Pro to develop neural network models to help you understand underlying processes and hidden linear and non-linear relationships for seemingly complex problems. Case studies demonstrate how to build neural networks, starting with a simple one-layer network.  Learn how to use JMP Pro to build more complicated self-learning and boosted models. In the process you’ll also learn how to build nonlinear principal components. 

This webinar covers: handling, building and validating models; handling hidden layers and nodes; gradient boosting; fitting options for transforming variables; and nonlinear principal components.

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