In Azure Machine Learning, registering a model is the standard process for storing and versioning a trained model within your workspace's model registry. When you register a model with a specific name, it is saved as version 1. If you subsequently train a new version of the model and register it using the same name, Azure Machine Learning automatically increments the version number (e.g., to version 2). This functionality is central to MLOps practices, as it allows you to track, organize, and manage the lifecycle of all your trained models, ensuring reproducibility and enabling you to select a specific version for deployment.

A. Provision an inference duster.

An inference cluster is a compute target used for deploying a model to perform real-time predictions, not for tracking or versioning the model asset itself.

B. Explain the model.

Explaining a model is part of Responsible AI and involves generating interpretations for its predictions. This process does not track or version the model.

D. Register the training data.

Registering data creates a versioned dataset in the workspace. While this tracks the data used for training, it does not track the resulting trained model.

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1. Microsoft Learn Documentation

"Manage models in Azure Machine Learning": Under the section "Register and track models

" it states

"Registering a model allows you to store and version your models in the Azure cloud

in your workspace. The model registry makes it easy to organize and keep track of your trained models."

2. Microsoft Learn Documentation

"Train and register a model with the CLI (v2)": In the "Register the model" section

the documentation explains

"Now that you've trained the model

you can register it in your workspace... Each time you register a model with the same name

the registry assumes it's a new version."

3. Microsoft Learn Documentation

"What is MLOps?": In the "Model registration" section of the MLOps lifecycle diagram

it is defined as: "Model registration is the act of storing and versioning a model in your Azure Machine Learning workspace." This confirms registration is the key step for versioning.