Anomaly Detection using the Matrix Profile

I like an excuse to play with fancy things, so when i first learned about the Matrix Profile for time series analysis, particularly around anomaly detection, i was intrigued. When i learned there was a nice python package (STUMPY) i could just pip install i was outright excited, as one thing i like more than … Continue reading Anomaly Detection using the Matrix Profile

Time series anomaly detection in Go using GoLearn

Output of the Go script. I've posted recently about learning just enough Go to be dangerous over the christmas break, well here is a update on my adventures so far. The below script (which is probably horrible in places if you know Go properly - tips welcome) uses goroutines to pull data from some REST … Continue reading Time series anomaly detection in Go using GoLearn

Anomaly Detection Resources

A list of useful Anomaly Detection resources, as I find interesting material I will add to this list. - "Awesome" time series anomaly detection list of GitHub. - YouTube playlist of interesting anomaly detection videos I maintain. - An interesting r/machinelearning thread. - Public Mendeley group for interesting Anomaly Detection papers. - KDD 2020 Tutorial … Continue reading Anomaly Detection Resources

Anomaly Detection Tutorial

always use a meme to kick off a tutorial Here is an anomaly detection tutorial that i created for my boss and the open source community where i work. It's part of some work i have been doing around adding some anomaly detection functionality into our open source monitoring project. Like most ML projects the … Continue reading Anomaly Detection Tutorial

Papers i’m reading #2

Continuation from this post. An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed CPS (Cyber Physical Systems). Link My Summary: Really interesting paper - PGM’s, HMM’s and all that good stuff. Quite complicated though and no clear route to implementation. Also I would wonder how well it scales beyond 10’s of time series. … Continue reading Papers i’m reading #2

Multi-Variate, Multi-Step, LSTM for Anomaly Detection

This post will walk through a synthetic example illustrating one way to use a multi-variate, multi-step LSTM for anomaly detection. Imagine you have a matrix of k time series data coming at you at regular intervals and you look at the last n observations for each metric. A matrix of 5 metrics from period t to t-n One approach … Continue reading Multi-Variate, Multi-Step, LSTM for Anomaly Detection