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Amazon SageMaker now offers new flexibility in configuring the model building pipelines

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Amazon SageMaker Pipelines, the first purpose built continuous integration and continuous delivery (CI/CD) service for machine learning (ML), now allows customers to specify custom dependencies between the steps of the model building pipeline. Previously, specifying the output of a step as the input to another was the only option for specifying the dependency and the execution order between the two steps of the model building pipeline. Now, customers have the option of explicitly listing the steps that a given step execution needs to wait on.

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