October 23, 2018
Duration: One Day Course
The Modeling Agency
Senior Consultant and Trainer
Regression, decision trees, neural networks – along with many other supervised learning techniques - provide powerful predictive insights. These data-driven insights inform which forces are shaping your organization’s outcomes. Once built, the models can produce key indicators to optimize the allocation of organizational resources.
New users of these established techniques are often impressed with how easy it all seems to be. Modeling software to build these models is widely available. However, proper data preparation is necessary to get optimal results. No amount of software automation can make up for poor manual data prep. Many fail toeven recognize that data prep was the problem. Theylikely conclude that the data was not capable of better performance. This one-day course will dedicate about half of its time on properly setting up and preparing the data for optimal performance during modeling.
The deployment phase includes proper model interpretation and looking for clues that the model will perform well on unseen data. Although the predictive power of these machine-learning models can be very impressive, there is no benefit unless they inform value-focused actions. Models must be deployed in an automated fashion to continually support decision making for residual impact. The instructor will show how to interpret supervised models with an eye toward decisioning automation. This course will demonstrate how real-world projects often combine different kinds of supervised models.
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