MLOps shouldn't stop at deployment
Get the most out of your deployed models with added transparency and control over model decisions, fostering trust and understanding through clear explanations for predictions.
Ensure stability of model performance
When your data changes so can your models predictions. Ensure accuracy by monitoring alteration.
Strengthen intuition for feature selection
Gain insights into how features influence model performance.
Derive a set of features and attributes for consistent prediction
Return the score that indicates the presence of features & instances that trick the model outcome.
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Start using Alibi Explain today through GitHub. You’ll only need a license for production use. It’s free for all non-production and academic uses.Â
Highlights
Feature Alteration
See how prediction changes and ensure stability of model performance against changing data.
Feature Impact
Alibi indicates how features influence model performance, strengthening intuition for feature selection.
Necessary Features
Focus on critical data attributes and features by deriving a set of features and attributes for consistent prediction.
Feature Attribution
Build confidence in integrity of model performance when Alibi illustrates prediction dynamics when features change.