yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
This helps data analysts and researchers identify unusual or suspicious data points within large, complex datasets. You input your tabular data, and it outputs scores indicating how much each data point deviates from the norm. This is designed for anyone who needs to find anomalies in multivariate data for tasks like fraud detection, quality control, or system monitoring.
9,747 stars. Used by 11 other packages. Actively maintained with 14 commits in the last 30 days. Available on PyPI.
Use this if you need a comprehensive and easy-to-use toolkit to find anomalies in various types of tabular data, from traditional statistical methods to modern deep learning techniques.
Not ideal if your primary focus is on time-series, graph, or natural language processing specific anomaly detection, as dedicated tools for those domains might offer more specialized features.
Stars
9,747
Forks
1,459
Language
Python
License
BSD-2-Clause
Category
Last pushed
Mar 01, 2026
Commits (30d)
14
Dependencies
6
Reverse dependents
11
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