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. - Creator of PyOD "yzhao062/anomaly-detection-resources" list of useful stuff. - An interesting r/machinelearning thread. - Public Mendeley group … Continue reading Anomaly Detection Resources
First stab at some Go (so hot right now)
It may be a combination of starting to go stir crazy over the Christmas break and some self loathing at the amount of FIFA i've been playing that's driven me to finally start learning some Go for a few data science and machine learning related projects i'm working on where it offers unique advantages. (In … Continue reading First stab at some Go (so hot right now)
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
Good Places For Datasets
I get asked this a lot by students so decided to make a little list in here that I can add to and point people towards. https://github.com/awesomedata/awesome-public-datasetshttps://www.kaggle.com/datasetshttps://datasetsearch.research.google.com/https://cloud.google.com/bigquery/public-datahttps://cloud.google.com/public-datasetshttps://registry.opendata.aws/https://data.world/data
Different types of time series anomalies
I find myself having to refer to this enough times that I decided to make a little infographic I can just more easily link to 🙂
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!
Market basket analysis in Python
An actual market basket I found in my Google photos. tl; dr; if you find yourself doing some association rule mining using mlxtend but finding it a bit slow then checkout PyFIM - here is a colab I made to get you started. I have recently been looking to do some market basket analysis ("Association … Continue reading Market basket analysis in Python
I helped build a thing!
don't mind if i do Here is a thing i helped build in work that i'm fairly happy with: https://www.linkedin.com/posts/andrewm4894_netdata-introducing-our-first-netdata-cloud-activity-6712008465574887424-SlIr Now, onto the next thing!
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
Premature Optimization
I've been doing some work that necessitated using the same statistical test from spicy lots of times on a fairly wide pandas dataframe with lots of columns. I spent a bit too much time googling around for the most efficient ways to do this, and even more time re-writing things various way before realizing i … Continue reading Premature Optimization