Model Versioning
The systematic practice of tracking and managing different iterations of machine learning models, including their code, data, configurations and performance metrics to enable reproducibility and rollback.
In plain language
Keeping a complete record of every version of your AI model so you can understand what changed, compare performance across versions and revert if something breaks. Think of it as Git for AI models.
Why this matters
Model versioning is a core governance requirement that allows you to maintain audit trails of all production AI changes. Without it, you cannot prove compliance, investigate failures or demonstrate responsible deployment. Australian regulators expect organisations to show they can trace model decisions and changes.
Relevance
GovernanceEnables audit trails, version control and rollback capabilities essential for demonstrating accountability and compliance in AI deployments.
Related terms
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