SeldonIO/alibi-detect

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2548 stars · 253 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Alibi Detect is a Python library providing algorithms for outlier, adversarial, and drift detection across tabular data, text, images, and time series. It supports both online and offline detectors with TensorFlow and PyTorch backends, aimed at monitoring machine learning models in production.

Use cases

• detect data drift in production ML models
• find outliers in tabular datasets
• detect concept drift in streaming data
• spot adversarial attacks on image classifiers
• monitor distribution shifts in text data
• detect anomalies in time series
• set up drift detection for deployed models

When to choose

• you need production-grade drift or outlier detection for ML pipelines
• you want both TensorFlow and PyTorch backend support
• you need detectors for mixed data types like images, text, and tabular data
• you are monitoring models in a MLOps setting

When to avoid

• you need a general-purpose anomaly detection toolkit outside ML monitoring
• you require a permissive open-source license (it uses Business Source License 1.1)
• you need lightweight detectors without deep learning dependencies

Facets

library · maturity active

machine-learning monitoring analytics machine-learning data-science artificial-intelligence monitoring python outlier-detection drift-detection adversarial-detection anomaly-detection model-monitoring tensorflow pytorch mlops

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