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

Streaming Anomaly Detection Solution by using Pub/Sub, Dataflow, BQML & Cloud DLP

Sherlock is an anomaly detection service built on top of Druid

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

A tool of detecting anomaly points from data

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

NETS:Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing

Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping

Machine learning Fraud Detection with SPARK and OCTAVE

My experiments in weaponizing ONOS applications (https://github.com/opennetworkinglab/onos)

Package implements decision tree and isolation forest

Package implements a number local outlier factor algorithms for outlier detection and finding anomalous data

Java implemented anomaly detection library.

Android app testing reaction times during awake brain surgeries

Package provide java implementation of outlier detection using normal distribution for multi-variate datasets

This repository contains code for running Dataflow pipelines for processing public Band Protocol data in Google Cloud Platform

Package provides the direct java conversion of the origin libsvm C codes as well as a number of adapter to make it easier to program with libsvm on Java

Java implementation of a Robust Random Cut Forest for streaming, unsupervised, adaptive anomaly detection

Dataflow pipeline for detecting anomalous transactions on the Ethereum and Bitcoin blockchains