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Predictive modeling is a core part of education in data science, business analytics, and other domains. JMP Pro includes machine learning algorithms commonly taught in this area, including decision trees, neural networks, support vector machines, k nearest neighbors, and more. It also includes tools for model tuning, validation, comparison, and deployment both inside and outside of JMP (e.g., in Python), and all are implemented in JMP's interactive, no-code interface that makes powerful techniques accessible to a wide range of students. This webinar demonstrates how to use JMP Pro's predictive modeling tools in the classroom and will highlight free teaching resources available to complement your course.