Full-stack data scientist interested in anything data-related. Basically how to leverage data to build cool things and entertain myself.
Particularly interested in applications of theory, building things end-to-end, and doing stuf from scratch. Preferably projects that combine 2/3 of these things.
They are a bit messy due to the nature of serving different purposes, being created at different times, written in different languages, etc. They come in the following types:
- Recent Projects. Stand-alone projects, mostly ML stuff. Name should be lower case separated by dashes, like-this. Should be largely simple and well-structured.
- Legacy Projects. Random repositories where I have dumped code I wrote before I started using GitHub. Project name in CamelCase, varying degree of just about everything in these. Largely not structured in a sensible way.
- Other. Random repos with no common thread.
- Haydn-Martin.github.io - new DS blog
- Perpetual_Prudence_Analysis - old personal finance/investing blog analysis in R
- Prob_Stat_ML - playing around with theory implementation in python and R
- Private. Either containing PI, secrets, not ready, personal, embarrassing, or top secret for super-secret reasons