outlier-detection

Anomaly detection related books, papers, videos, and toolboxes

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

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

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

TODS: An Automated Time-series Outlier Detection System

A Python Library for Graph Outlier Detection (Anomaly Detection)

fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.

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 Deep Graph-based Toolbox for Fraud Detection

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

Official Implement of "ADBench: Anomaly Detection Benchmark".

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

Benchmarking Generalized Out-of-Distribution Detection

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

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

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

An End-to-end Outlier Detection System