Model Versioning & Experiment Tracking
Manage different AI model versions and track experiments for better reproducibility and comparison.
Why Track AI Models?
Imagine you're developing an AI model, constantly tweaking it to improve performance. How do you keep track of all your changes?
This lesson introduces Model Versioning and Experiment Tracking – essential practices for managing the lifecycle of your AI models.
What is Model Versioning?
Model versioning is like keeping different saved drafts of a document as you work on it. Each draft represents a specific state or iteration of your AI model.
It ensures that you can always go back to a previous version if a new one doesn't perform as expected, or if you need to reproduce past results.
All lessons in this course
- Model Versioning & Experiment Tracking
- A/B Testing AI Models
- Monitoring Model Performance
- Detecting and Handling Model Drift