Amazon Redshift ML simplifies the use of machine learning (ML) by using simple SQL statements to create and train ML models from data in Amazon Redshift. You can use Amazon Redshift ML to solve binary classification, multi-class classification, and regression problems and can use either AutoML or XGBoost directly.
This post is part of a series that describes the use of Amazon Redshift ML. For more information about building regression using Amazon Redshift ML, see Build regression models with Amazon Redshift ML.
You can use Amazon Redshift ML to automate data preparation, pre-processing, and selection of problem type as depicted in this blog post. We assume that you have a good understanding of your data and what problem type is most applicable for your use case. This post specifically focuses on creating models in Amazon Redshift using the multi-class classification problem type, which consists on classifying instances into one of three

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