Anomaly Open Source Projects

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

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

机器学习算法python实现

Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.

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

A curated list of awesome anomaly detection resources

What are the differences between the transaction isolation levels in databases? This is a suite of test cases which differentiate isolation levels.

Algorithms for outlier, adversarial and drift detection

It'll detect your anomalies! Part of the Kale stack.

The Numenta Anomaly Benchmark

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

A framework for secure and scalable network traffic analysis - https://netcap.io

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

Collection of slides, repositories, papers about AIOps

A machine learning toolkit for log-based anomaly detection [ISSRE'16]

Samples for TensorRT/Deepstream for Tesla & Jetson

Kibana Alert & Report App for Elasticsearch

RNN based Time-series Anomaly detector model implemented in Pytorch.

Anomaly Detection and Correlation library

A Python toolkit for rule-based/unsupervised anomaly detection in time series

A Java package to automatically detect anomalies in large scale time-series data

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

list of papers, code, and other resources

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

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

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)

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

A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps

A PyTorch implementation of the Deep SVDD anomaly detection method

Library for exploring and validating machine learning data

A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

CICFlowmeter-V4.0 (formerly known as ISCXFlowMeter) is an Ethernet traffic Bi-flow generator and analyzer for anomaly detection that has been used in many Cybersecurity datsets such as Android Adware-General Malware dataset (CICAAGM2017), IPS/IDS dataset (CICIDS2017), Android Malware dataset (CICAndMal2017) and Distributed Denial of Service (CICDDoS2019).

Black-box transactional safety checker based on cycle detection

Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

Interactive Azure Sentinel Notebooks provides security insights and actions to investigate anomalies and hunt for malicious behaviors.

A newer more updated version of the prometheus anomaly detector (https://github.com/AICoE/prometheus-anomaly-detector-legacy)

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

Anomaly detection

iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

Applied generative adversarial networks (GANs) to do anomaly detection for time series data

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

An Integrated Experimental Platform for time series data anomaly detection.

A complete list of papers on anomaly detection.

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.

Extended Isolation Forest for Anomaly Detection

This is an unofficial implementation of the paper “PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization”.

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

log anomaly detection toolkit including DeepLog

Machine-readable references of terms defined in web browser specifications

Pytorch Implementation of DeepLog.