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Amazon Web Services (AWS) has made its data warehouse product Redshift ML generally available, including in Asia Pacific.
According to AWS, Amazon Redshift ML enables developers to create, train and deploy machine learning (ML) models using SQL commands. The move allows users to “leverage” Amazon SageMaker, a managed ML service, without moving data or learning a new skill, AWS claimed.
Writing in a blog post, the cloud giant said Amazon Redshift ML automatically discovers the best model and tunes it based on training data using Amazon SageMaker Autopilot. This chooses between regression, binary or multi-class classification models.
“Amazon Redshift ML uses your parameters to build, train and deploy the model in the Amazon Redshift data warehouse,” AWS said.
“You can obtain predictions from these trained models using SQL queries as if you were invoking a user-defined function (UDF) and leverage all benefits of Amazon Redshift, including massively parallel processing capabilities. You can also import your pre-trained SageMaker Autopilot, XGBoost or MLP models into your Amazon Redshift cluster for local inference.”
The tool is available in the company's Asia Pacific Singapore and Sydney regions.
