Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for machine learning (ML), is now integrated with SageMaker’s automatic model tuning capability. Customers can add a model tuning step (TuningStep) in their SageMaker Pipelines which will automatically invoke a hyperparameter tuning job. The hyperparameter tuning finds the best version of a model by running many training jobs on the dataset using the algorithm and the ranges of hyperparameters specified by the customer. They can then register the best version of the model into the model registry using the RegisterModel step.

Categories: AWS