This module will focus on the ensemble methods decision trees, bagging, and random forests, which combine multiple models to improve prediction accuracy and reduce overfitting. Decision Trees are a ...

Decision trees are easy to understand and dissect. They're useful when you need to make a decision quickly. This is the model that is used the most in statistical analysis. Use it when you want to ...

This course examines a modern treatment of statistical learning in various decision-making settings. Students will explore both supervised and unsupervised learning, data preprocessing, model ...