Machine Learning with Tree-Based Models in R
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Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.
Tree-based machine learning models can reveal complex non-linear relationships in data and often dominate machine learning competitions. In this course, you’ll use the tidymodels package to explore and build different tree-based models—from simple decision trees to complex random forests. You’ll also learn to use boosted trees, a powerful machine learning technique that uses ensemble learning to build high-performing predictive models. Along the way, you’ll work with health and credit risk data to predict the incidence of diabetes and customer churn.
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Machine Learning/AI Engineer
Machine Learning/AI Engineers build end-to-end ML applications and power many of the apps we use every day. They work in Python, Git, & ML.
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