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

Numpy Feature Engineering – 2x Speed Up Over Pandas!

The Setup This is a little one I was surprised to see. Recently I had a need to do some pretty basic feature engineering to a pandas dataframe prior to training some models. Basically I needed to take differences of each column, apply some smoothing, and then add a number of lagged columns for each … Continue reading Numpy Feature Engineering – 2x Speed Up Over Pandas!

Time series clustering with tslearn

I've recently been playing around with some time series clustering tasks and came across the tslearn library. I was interested in seeing how easy it would be to get up and running some of the clustering functionality that is already built into tslearn, turns out it was quite easy and straight forward, perfect blog post … Continue reading Time series clustering with tslearn

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