Part 3:Deploying Models with Redshift ML

Part 3 introduces you to more ways to leverage Amazon Redshift ML. You will learn about deep learning algorithms, how to train a customized model, and how you can use models trained outside of Amazon Redshift to run inference queries in your data warehouse.

This part closes with an introduction to time-series forecasting, how to use it with Amazon Redshift ML, and how you can optimize and easily re-train your models.

This part comprises the following chapters:

• Chapter 9, Deep Learning with Redshift ML
• Chapter 10, Creating Custom ML Models with XGBoost
• Chapter 11, Bring Your Own Models for In-Database Inference
• Chapter 12, Time-Series Forecasting in Your Data Warehouse
• Chapter 13, Operationalizing and Optimizing Amazon Redshift ML Models