yzhao062/pyod
PyOD is a comprehensive Python library for multi-modal anomaly detection, offering 60+ detectors and an agentic workflow for AI agents to drive investigations across various data types.
Awesome AI for Infra › Anomaly Detection
sintel-dev/Orion
Orion is a specialized machine learning library designed for unsupervised time series anomaly detection. Developed by the Data to AI Lab at MIT, it provides a collection of 'verified' ML pipelines that automatically identify unusual patterns in time series data, flagging them for human review. The library leverages automated machine learning techniques to streamline the process of building and deploying anomaly detection models. It offers several pre-built pipelines, including AER, TadGAN, and LSTM-based methods, allowing users to select and apply different AI algorithms for detecting anomalies. Orion supports fitting these pipelines to training data and then using them to detect anomalies in new, incoming time series. The project also features a benchmark system and a leaderboard, openly comparing the performance of its various pipelines across different datasets. While Orion provides a general-purpose library, its core utility lies in identifying abnormalities in operational time series, making it directly applicable to AIOps scenarios for detecting incidents or performance deviations.
https://github.com/sintel-dev/Orion
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