Alibi Detect

Alibi Detect is a source-available Python library focused onoutlier,adversarial anddrift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. BothTensorFlow andPyTorch backends are supported for drift detection.

For more background on the importance of monitoring outliers and distributions in a production setting, check outthis talk from theChallenges in Deploying and Monitoring Machine Learning Systems ICML 2020 workshop, based on the paperMonitoring and explainability of models in production and referencing Alibi Detect.

For a thorough introduction to drift detection, check out the talk below titled,Protecting Your Machine Learning Against Drift: An Introduction. The talk covers what drift is and why it pays to detect it, the different types of drift, how it can be detected in a principled manner and also describes the anatomy of a drift detector.

Last updated4 months ago