3202 - Classification Using Tree Models - 2021

Issued by GAIn® - The Global AI network

This two-day badge training starts with an explanation of why and when to use tree classification techniques. Three techniques are explained and practiced in depth: Random Forest, AdaBoost, and XGBoost. For each technique, you learn the criteria to determine whether a model is suited for your data and how to evaluate the results.

Skills

Earning Criteria

Decision Tree - Understanding tree classification models through the explanation of simple decision trees and hands-on experience.
Random Forest - Learning to apply a bagging tree classification technique through hands-on experience.
AdaBoost - Learning to apply a boosting tree classification technique through hands-on experience.
XGBoost - Gaining a deeper understanding of the most popular boosting tree method, frequently used to win data science competitions.
Model selection - Identifying the advantages and disadvantages of different classification models and when to apply them.
Exam