claude

sagemaker-auto-research

Autonomous ML experimentation loops on Amazon SageMaker — Redshift data to a registered model that meets a success metric.

0 on GitHubby rddefauwv0.1.0MITupdated 24 days ago

Not in a marketplace yet, so it loads for one session with --plugin-dir.

Plugin sagemaker-auto-research in aws-samples/sample-sagemaker-autoresearch. Commands read from the repo's manifest — 19 days ago.

What it installs

Skills (1)

  • sagemaker-auto-research

    Use when the user wants to run an autonomous ML experimentation loop on Amazon SageMaker — from Redshift data through feature engineering, training, MLflow tracking, and model registration — until a model meets a success metric (e.g. F1 >= 0.9). Triggers on "auto research", "run experiments until",

Slash commands (1)

  • /sagemaker-auto-research:sm-research

    Set up and launch a SageMaker auto-research run — interview for goal/data/criteria, scaffold research.yaml, then run the loop until a model meets the goal or a guardrail stops it.

View source on GitHub

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