Anomaly detection related books, papers, videos, and toolboxes
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Updated
Apr 23, 2024 - Python
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
ELKI Data Mining Toolkit
A curated list of graph-based fraud, anomaly, and outlier detection papers & resources
TODS: An Automated Time-series Outlier Detection System
A Deep Graph-based Toolbox for Fraud Detection
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.
A Python Library for Graph Outlier Detection (Anomaly Detection)
A python library for time-series smoothing and outlier detection in a vectorized way.
Benchmarking Generalized Out-of-Distribution Detection
ML powered analytics engine for outlier detection and root cause analysis.
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.
Luminaire is a python package that provides ML driven solutions for monitoring time series data.
GAAL-based Outlier Detection
ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.
Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection, semi-supervised anomaly detection
SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.
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