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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.
Anogan Tf
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
Ee Outliers
Open-source framework to detect outliers in Elasticsearch events
Spark Iforest
Isolation Forest on Spark
Hastic Grafana App
Hastic data management server for labeling patterns and anomalies in Grafana
Deep Svdd
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.
Anogan Keras
Unsupervised anomaly detection with generative model, keras implementation
Kitnet Py
KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.
Deep Sad Pytorch
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Adaptive Alerting
Anomaly detection for streaming time series, featuring automated model selection.
A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.
Anomaly Detection In Surveillance Videos
Real-World Anomaly Detection in Surveillance Videos
Isolation Forest
A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.
Repo 2019
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
Skip Ganomaly
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.
Keras Oneclassanomalydetection
[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.
Visual Feature Attribution Using Wasserstein Gans Pytorch
Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, 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.
Find big moving stocks before they move using machine learning and anomaly detection
Coursera Ml Py
Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera
Anomaly Detection
A machine learning plugin in Open Distro for Elasticsearch for real time anomaly detection on streaming data.
Repository for the Explainable Deep One-Class Classification paper
Anomaly detection
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.
Machine Failure Detection
PCA and DBSCAN based anomaly and outlier detection method for time series data.
Awesome Aiops
Junos monitoring with healthbot
Healthbot configuration examples. Scripts to manage Healthbot. Closed loop automation. Healthbot building blocks description and troubleshooting guide
Anomaly Detection and Correlation library
T Bear
Detect EEG artifacts, outliers, or anomalies using supervised machine learning.
A log analysis toolkit for automated anomaly detection [ISSRE'16]
Getting Things Done With Pytorch
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.
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