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conda-forge.org : alibi-detect
[Alibi Detect](https://github.com/SeldonIO/alibi-detect) is an open source 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. - [Documentation](https://docs.seldon.io/projects/alibi-detect/en/latest/) 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. For a thorough introduction to drift detection, check out [Protecting Your Machine Learning Against Drift: An Introduction](https://youtu.be/tL5sEaQha5o). he 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. PyPI: [https://pypi.org/project/alibi-detect/](https://pypi.org/project/alibi-detect/)
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purl: pkg:conda/alibi-detect
Keywords: adversarial, anomaly, concept-drift, data-drift, detection, drift-detection, images, outlier, semi-supervised-learning, tabular-data, text, time-series, unsupervised-learning
License: Apache-2.0
Latest release: over 1 year ago
First release: over 2 years ago
Stars: 1,747 on GitHub
Forks: 174 on GitHub
See more repository details: repos.ecosyste.ms
Last synced: 22 days ago