Create Experiment
sagemaker_create_experiment | R Documentation |
Creates a SageMaker experiment¶
Description¶
Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use
the search
API to search for the tags.
To add a description to an experiment, specify the optional
Description
parameter. To add a description later, or to change the
description, call the update_experiment
API.
To get a list of all your experiments, call the list_experiments
API.
To view an experiment's properties, call the describe_experiment
API.
To get a list of all the trials associated with an experiment, call the
list_trials
API. To create a trial call the create_trial
API.
Usage¶
Arguments¶
ExperimentName
[required] The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
DisplayName
The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify
DisplayName
, the value inExperimentName
is displayed.Description
The description of the experiment.
Tags
A list of tags to associate with the experiment. You can use
search
API to search on the tags.
Value¶
A list with the following syntax: