Hugging Face Text Classification Quickstart

I have been working a bit lately with some text classification stuff using Hugging Face - its great n all but their docs can actually be a bit overwhelming. So here is a minimal text classification example, using huggingface and either pytorch or tensorflow (you decide). Will try to update and maintain the colab here: … Continue reading Hugging Face Text Classification Quickstart

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

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

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!