Open source library for Experiment Tracking in SageMaker Jobs and Notebooks
Project description
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.
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