Take your SageMaker models into production.
What it does
Selects, customizes, evaluates, and deploys models on Amazon SageMaker, and diagnoses deployed endpoints.
When to use it
Use for model selection, fine-tuning, training-data preparation, evaluation, deployment, inference optimization, or SageMaker endpoint troubleshooting.
How to use it
Give it a model-training or deployment request; it follows the relevant workflow to run jobs or deploy models in your cloud account.
Uses
AS
AB
Good to know
- cannot be undone: SageMaker Managed MLflow
Latest review
What you need · 1
The packaged transformation tooling runs with Python 3.
Access · 5
This skill
SageMaker Managed MLflow
Write
Creates or deletes MLflow apps (irreversible)
S3
Write
Uploads transformation code and results
Bedrock
Execute
Deploys a customized Nova model
Write
Sends a test inference prompt