This repository contains a presentation for a 1 hour lecture given to the NYC Insight Data Science Summer 2018 cohort. The content (hopefully) provides a thorough analysis of Classification and Regression Trees (CART), covering topics like:
- Decision Trees
- Random Forest + Bagging.
- Mechanics of how a tree is built (gini impurity).
- Regularization
- Strenghts and Weaknesses of CART algorithms.
The slides are made deliberately verbose so that an interested user can still learn the material without having heard my presentation.