datamllab/tods
TODS is a comprehensive automated machine learning system for multivariate time-series outlier detection, providing modules for preprocessing, feature extraction, and a wide array of detection algo...
Awesome AI for Infra › Anomaly Detection
yzhao062/pyod
PyOD (Python Outlier Detection) is a powerful, open-source Python library dedicated to comprehensive anomaly detection across diverse data modalities including tabular, time series, graph, text, image, and audio. It provides over 60 anomaly detection algorithms, making it one of the most extensive libraries of its kind. A key feature of PyOD 3 is its "agentic" capabilities, allowing AI agents like Claude Code or other MCP-compatible LLMs to interact with the library through skills like 'od-expert' for natural language-driven anomaly detection investigations. The library includes ADEngine, an orchestration core that can automatically select, compare, and assess appropriate detectors. While offering a classic API for direct detector application, PyOD also provides an advanced layer where agents can query detector knowledge, plan detection strategies, and explain findings. PyOD's utility extends to various operational scenarios by helping identify unusual patterns in system metrics, logs, and other IT data, which is crucial for incident detection, security monitoring, and predictive maintenance within AIOps contexts. The project emphasizes multi-modal detection, full lifecycle support from raw data to explained anomalies, and integration with agent-based workflows, bridging advanced anomaly detection with intelligent automation for IT operations.
https://github.com/yzhao062/pyod
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