Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

List of tools & datasets for anomaly detection on time-series data.

fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both images and labels, while significantly reducing data operation costs, all with unmatched scalability.

A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources

TODS: An Automated Time-series Outlier Detection System

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

A Python Library for Graph Outlier Detection (Anomaly Detection)

Benchmarking Generalized Out-of-Distribution Detection

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, books, videos, articles and open-source libraries etc

ELKI Data Mining Toolkit

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

ML powered analytics engine for outlier detection and root cause analysis.

A python library for time-series smoothing and outlier detection in a vectorized way.

A Deep Graph-based Toolbox for Fraud Detection

Curated list of open source tooling for data-centric AI on unstructured data.

Deep learning-based outlier/anomaly detection

The Official Repository for "Generalized OOD Detection: A Survey"

ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.

(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)

SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.

Bayesian Coherent Point Drift / Domain Elastic Transform

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

An End-to-end Outlier Detection System

A distributed Spark/Scala implementation of the isolation forest algorithm for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.

(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

Anomaly detection for streaming time series, featuring automated model selection.