XGBoost for Regression Predictive Modeling and Time Series Analysis

Table of Contents

1. An Overview of Machine Learning, Classification, and Regression
2. XGBoost Quick Start Guide with an Iris Data Case Study
3. Demystifying the XGBoost Paper
4. Adding On to the Quick Start – Switching Out the Dataset with a Housing Data Case Study
5. Classification and Regression Trees, Ensembles, and Deep Learning Models – What's Best for Your Data?
6. Data Cleaning, Imbalanced Data, and Other Data Problems
7. Feature Engineering
8. Encoding Techniques for Categorical Features
9. Using XGBoost for Time Series Forecasting
10. Model Interpretability, Explainability, and Feature Importance with XGBoost
11. Metrics for Model Evaluations and Comparisons
12. Managing a Feature Engineering Pipeline in Training and Inference
13. Deploying Your XGBoost Model