How to: Industry-strength Anomaly Detection
* [Alibi Detect](https://github.com/SeldonIO/alibi-detect) ![](https://img.shields.io/github/stars/SeldonIO/alibi-detect.svg?cacheSeconds=86400) - alibi-detect is a Python package focused on outlier, adversarial and concept drift detection.
* [Darts](https://github.com/unit8co/darts) ![](https://img.shields.io/github/stars/unit8co/darts.svg?cacheSeconds=86400) - Darts is a library for user-friendly forecasting and anomaly detection on time series.
* [Deequ](https://github.com/awslabs/deequ) ![](https://img.shields.io/github/stars/awslabs/deequ.svg?cacheSeconds=86400) - A library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
* [PyOD](https://github.com/yzhao062/pyod) ![](https://img.shields.io/github/stars/yzhao062/pyod.svg?cacheSeconds=86400) - A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
* [TFDV](https://github.com/tensorflow/data-validation) ![](https://img.shields.io/github/stars/tensorflow/data-validation.svg?cacheSeconds=86400) - TFDV (Tensorflow Data Validation) is a library for exploring and validating machine learning data.