What are the best practices for model versioning in AI?

What are the best practices for model versioning in AI?

Best practices for model versioning include using a consistent naming convention, maintaining a changelog, and utilizing version control systems like Git.

Why is it important to have a changelog?

A changelog helps track changes, improvements, and bug fixes over time, making it easier to understand the evolution of the model.

Can you recommend any tools for version control?

Sure! Popular tools for version control include Git, DVC (Data Version Control), and MLflow, which are specifically designed for machine learning.

How often should I update my model versions?

You should update your model versions whenever there are significant changes, such as new data, improved algorithms, or bug fixes.

What challenges might I face with model versioning?

Challenges include managing dependencies, ensuring reproducibility, and coordinating updates across teams.