From 949d9702bdbb3230455dd47440979761553c0c34 Mon Sep 17 00:00:00 2001 From: Max Lowther Date: Mon, 12 Feb 2024 11:41:53 +0000 Subject: [PATCH] Update README.md (#877) --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index fe623117b..52a71d8e9 100644 --- a/README.md +++ b/README.md @@ -25,7 +25,7 @@ --- -[Alibi Detect](https://github.com/SeldonIO/alibi-detect) is an 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. +[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. * [Documentation](https://docs.seldon.io/projects/alibi-detect/en/stable/) 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.