This chapter covers
- A review of the end-to-end gradient boosting example from chapter 7
- A comparison of the results of the gradient boosting example from chapter 7 with a deep learning solution for the same problem
- The result of ensembling a gradient boosted model with a deep learning model
In chapter 7, we did an in-depth exploration of an end-to-end example of using gradient boosting. We explored a dataset of Airbnb listings for Tokyo, we engineered features suitable for a pricing regression task, and then we created a baseline model trained on this dataset to predict prices. Finally, applying the techniques we had learned in the book up to that point, we optimized an XGBoost model trained on this dataset and examined some approaches to explain the behavior of the model.