Course Introduction
What is XGBoost?
Demo: XGBoost Pima Indian Diabetes
Summary
Section Introduction
Gradient Boosting and the Decision Tree
Recursive Binary Splitting
Demo: Label Encoding with XGBoost
Ensembles
Bagging and Boosting
Demo: Kfold Cross Validation with XGBoost
Summary
Section Introduction
Demo: Handling Missing Data
Demo: Serialize a Model with Pickle
Demo: Importance Scores using XGBoost
Demo: Caution using Importance Scores in XGBoost
Demo: Monitor Model Performance
Demo: Model Evaluation using Learning Curves
Demo: Early Stopping in XGBoost
Demo: Regression Model in XGBoost
Demo: Parallelism in XGBoost
Demo: Hyperparameter Default Recommendations
Demo: Tuning the Number of Decision Trees
Demo: Tuning Row Subsampling
Demo: Tuning the Learning Rate
Demo: Kaggle Top Titanic Model
Summary
