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| stage | group | info | title |
|---|---|---|---|
| ModelOps | MLOps | To determine the technical writer assigned to the Stage/Group associated with this page, see https://handbook.gitlab.com/handbook/product/ux/technical-writing/#assignments | MLOps |
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- Tier: Free, Premium, Ultimate
- Offering: GitLab.com, GitLab Self-Managed, GitLab Dedicated
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GitLab Machine Learning Operations (MLOps) is set of tools designed to help with your machine learning workflows.
GitLab MLOps features include:
- Model registry: Manage your machine learning models, along with associated metadata such as parameters, performance metrics, artifacts, and logs. For more information, see model registry.
- Model experiments: Track and manage machine learning experiments in GitLab. An experiment is a collection of comparable model candidates, which are variations of the training of a machine learning model. For more information, see model experiments.
GitLab MLOps Python client
GitLab offers a Python client to interact with the GitLab MLOps features.
For details, see the GitLab MLOps Python client.