Creating a Custom ML Model with XGBoost
So far, all of the supervised learning models we have explored have utilized the Amazon Redshift Auto ML feature, which uses Amazon SageMaker Autopilot behind the scenes. In this chapter, we will explore how to create custom machine learning (ML) models. Training a custom model gives you the flexibility to choose the model type and the hyperparameters to use. This chapter will provide examples of this modeling technique. By the end of this chapter, you will know how to create a custom XGBoost model and how to prepare the data to train your model using Redshift SQL.
In this chapter, we will go through the following main topics:
- Introducing XGBoost
- Introducing an XGBoost use case
- XGBoost model with Auto off feature
