Suod(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)
PynomalyAnomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
BanpeiAnomaly detection library based on singular spectrum transformation(sst)
AiopstoolsThe fundamental package for AIops with python.
Anogan TfUnofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)
TaganomalyAnomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
DeeplogPytorch Implementation of DeepLog.
MidasGo implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams
Ee OutliersOpen-source framework to detect outliers in Elasticsearch events
Hastic Grafana AppHastic data management server for labeling patterns and anomalies in Grafana
Deep SvddRepository for the Deep One-Class Classification ICML 2018 paper
RemixautomlR package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.
Anogan KerasUnsupervised anomaly detection with generative model, keras implementation
Kitnet PyKitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.
Deep Sad PytorchA PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Adaptive AlertingAnomaly detection for streaming time series, featuring automated model selection.
StumpySTUMPY is a powerful and scalable Python library for modern time series analysis
MatrixprofileA Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.
PyoddsAn End-to-end Outlier Detection System
Isolation ForestA Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.
Repo 2019BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics
Log3cLog-based Impactful Problem Identification using Machine Learning [FSE'18]
OpenubaA 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]
Logdeeplog anomaly detection toolkit including DeepLog
CsiCSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)
ForemastForemast adds application resiliency to Kubernetes by leveraging machine learnt patterns of application health to keep applications healthy and stable
Pytorch cppDeep Learning sample programs using PyTorch in C++
GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
DeepaiDetection 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.
PysadStreaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)
BayesloopProbabilistic programming framework that facilitates objective model selection for time-varying parameter models.
MlA high-level machine learning and deep learning library for the PHP language.
SentinlKibana Alert & Report App for Elasticsearch
SurpriverFind big moving stocks before they move using machine learning and anomaly detection
TimecopTime series based anomaly detector
Coursera Ml PyPython programming assignments for Machine Learning by Prof. Andrew Ng in Coursera
Anomaly DetectionA machine learning plugin in Open Distro for Elasticsearch for real time anomaly detection on streaming data.
Repo 2017Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
FcddRepository for the Explainable Deep One-Class Classification paper
Anomaly detectionThis 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.
UgfraudAn Unsupervised Graph-based Toolbox for Fraud Detection
Junos monitoring with healthbotHealthbot configuration examples. Scripts to manage Healthbot. Closed loop automation. Healthbot building blocks description and troubleshooting guide
LuminolAnomaly Detection and Correlation library
T BearDetect EEG artifacts, outliers, or anomalies using supervised machine learning.
Datastream.ioAn open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana
LoglizerA log analysis toolkit for automated anomaly detection [ISSRE'16]
Getting Things Done With PytorchJupyter 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.