Top 160 anomaly-detection open source projects

(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].

Anomaly detection library based on singular spectrum transformation(sst)

The fundamental package for AIops with python.

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

Pytorch Implementation of DeepLog.

Go implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

Anomaly detection for temporal data using LSTMs

Open-source framework to detect outliers in Elasticsearch events

Log Anomaly Detection - Machine learning to detect abnormal events logs

Isolation Forest on Spark

Hastic data management server for labeling patterns and anomalies in Grafana

Repository for the Deep One-Class Classification ICML 2018 paper

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

Unsupervised anomaly detection with generative model, keras implementation

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

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

Latent space autoregression for novelty detection.

STUMPY is a powerful and scalable Python library for modern time series analysis

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

An End-to-end Outlier Detection System

Abnormal Event Detection in Videos using SpatioTemporal AutoEncoder

Real-World Anomaly Detection in Surveillance Videos

A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.

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

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

Log-based Impactful Problem Identification using Machine Learning [FSE'18]

A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for Security Analytics. Developed with luv by Data Scientists & Security Analysts from the Cyber Security Industry. [PRE-ALPHA]

log anomaly detection toolkit including DeepLog

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

Foremast adds application resiliency to Kubernetes by leveraging machine learnt patterns of application health to keep applications healthy and stable

Deep Learning sample programs using PyTorch in C++

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Source code for Skip-GANomaly paper

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

A curated list of awesome anomaly detection resources

Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch

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

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

A high-level machine learning and deep learning library for the PHP language.

Kibana Alert & Report App for Elasticsearch

Find big moving stocks before they move using machine learning and anomaly detection

Time series based anomaly detector

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

A machine learning plugin in Open Distro for Elasticsearch for real time anomaly detection on streaming data.

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Repository for the Explainable Deep One-Class Classification paper

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

An Unsupervised Graph-based Toolbox for Fraud Detection

PCA and DBSCAN based anomaly and outlier detection method for time series data.

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

Healthbot configuration examples. Scripts to manage Healthbot. Closed loop automation. Healthbot building blocks description and troubleshooting guide

Anomaly Detection and Correlation library

Detect EEG artifacts, outliers, or anomalies using supervised machine learning.

An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana

A log analysis toolkit for automated anomaly detection [ISSRE'16]

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.