Managing Amazon Redshift ML
Amazon Redshift ML enables Amazon Redshift users to create, deploy, and execute ML models using familiar SQL commands. Amazon Redshift has built-in integration with Amazon SageMaker Autopilot, which chooses the best ML algorithm based on your data using its automatic algorithm selection capabilities. It enables users to run ML algorithms without the need for expert knowledge of ML. On the other hand, ML experts such as data scientists have the flexibility to select algorithms such as XGBoost and specify the hyperparameters and preprocessors. Once the ML model has been deployed in Amazon Redshift, you can run the prediction using SQL at scale. This integration completely simplifies the pipeline, which is required to create, train, and deploy the model for prediction. Amazon Redshift ML allows you to create, deploy, and predict using the data in the data warehouse, as follows:
Figure 10.1 – Amazon Redshift ML capabilities
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