For the last several years, I have been interested in and actively tinkering with algorithmic stock trading, quantatative analysis, and machine learning / AI in general.

This Jupyter notebook provides a basic example of the type of timeseries computation I have been able to do to calculate various financial indicators and to do exploratory data analysis. In this case, the aim was to analyze past stock data I had paid for from Nasdaq Datalink to try and find oversold conditions to exploit for short/medium term profit.

I used a Google Cloud Platform free trial along with their Storage and DataProc services to temporarily commission a cluster of VMs on which I could run an Apache Spark (via PySpark) cluster - as calculations became untenable on my desktop computer.