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[Alibi Detect](https://github.com/SeldonIO/alibi-detect) is a Python library focused on **outlier**, **adversarial** and **drift** detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both **TensorFlow** and **PyTorch** backends are supported for drift detection.
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[Alibi Detect](https://github.com/SeldonIO/alibi-detect) is a source-available Python library focused on **outlier**, **adversarial** and **drift** detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both **TensorFlow** and **PyTorch** backends are supported for drift detection.
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* [Documentation](https://docs.seldon.io/projects/alibi-detect/en/stable/)
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For more background on the importance of monitoring outliers and distributions in a production setting, check out [this talk](https://slideslive.com/38931758/monitoring-and-explainability-of-models-in-production?ref=speaker-37384-latest) from the *Challenges in Deploying and Monitoring Machine Learning Systems* ICML 2020 workshop, based on the paper [Monitoring and explainability of models in production](https://arxiv.org/abs/2007.06299) and referencing Alibi Detect.

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