Covers: implementation of How to store ML Models
Estimated time needed to finish: 20 minutes
Questions this item addresses:
  • How to register a ML Model in sagemaker?
  • How are models grouped?
  • How to deploy a model?
How to use this item?

Sagemaker models are versioned and stored under groups, these are either 1 to 1 with your model type, OR with the problem you're trying to solve. Within the link you have many subpages that go through the main ways to use the sagemaker repository. They can be accessed both via Sagemaker studio and via boto3.

Author(s) / creator(s) / reference(s)
Amazon
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Recipe
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Registering ML Models

Collaborators
Total time needed: ~38 minutes
Objectives
To learn how models can be stored, tracked and collaborated on.
Potential Use Cases
Repeatable and collaborative ML projects
Who is this for ?
INTERMEDIATEMachine learning engineers and data scientists who are looking on how to store and iterate on their models.
Click on each of the following annotated items to see details.
ARTICLE 1. How to build a ML Model Registry
  • Why have a ML Registry?
  • How to build a ML registry yourself?
7 minutes
ARTICLE 2. Storing ML Models in Sagemaker
  • How to register a ML Model in sagemaker?
  • How are models grouped?
  • How to deploy a model?
20 minutes
ARTICLE 3. Storing ML Models in Azure ML
  • How to register a ML Model in Azure ML?
  • How to tag models in Azure ML?
5 minutes
WRITEUP 4. Storing ML Models in ML Flow.
  • How to register a ML Model in ML Flow?
5 minutes
WRITEUP 5. Why do we need a ML Model registry?
  • Why do you need a ML Model Registry?
1 minutes

Concepts Covered

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