One of the hottest predictive analytics algorithms this year is gradient-boosted trees. One cannot hope to understand why it is popular and successful if one doesn't understand the basics of decision trees. Specific tree algorithms have risen and fallen in popularity, but the core concepts have been fundamental to the discipline for at least 30 years. In this course, instructor Keith McCok demonstrates and discusses a half-dozen popular decision tree algorithms. Keith shows how to access them using other open-source options from within the K platform. He explains them and reverse eeers them to create a solid foundation on which to build more advanced data science skills.

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