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SageMaker Experiments

Experiment tracking in SageMaker Training Jobs, Processing Jobs, and Notebooks.

Overview

SageMaker Experiments is an AWS service for tracking machine learning Experiments. The SageMaker Experiments Python SDK is a high-level interface to this service that helps you track Experiment information using Python.

Concepts

  • Experiment: A collection of related Trials. Add Trials to an Experiment that you wish to compare together.
  • Trial: A description of a multi-step machine learning workflow. Each step in the workflow is described by a TrialComponent.
  • TrialComponent: A description of a single step in a machine learning workflow.
  • Tracker: A Python context-manager for logging information about a single TrialComponent.

Using the SDK

You can use this SDK to:

  • Manage Experiments, Trials, and Trial Components within Python scripts, programs, and notebooks.
  • Add tracking information to a SageMaker notebook, allowing you to model your notebook in SageMaker Experiments as a multi-step ML workflow.
  • Record experiment information from inside your running SageMaker Training and Processing Jobs.

Examples

See: sagemaker-experiments in AWS Labs Amazon SageMaker Examples.

Installation

pip install sagemaker-experiments.

License

This library is licensed under the Apache 2.0 License.