Jordan Barker’s site is a personal project portfolio maintained by an AI engineer. Rather than a company homepage, it functions as a working notebook made public: each entry pairs a short description with a category tag such as Games, Simulation, Hardware, or Data analysis, and a year. The overall tone is practical and understated, reflecting an engineer documenting side projects rather than marketing them.
The projects cluster around several themes. Machine learning and Bayesian reasoning appear in the Secret Hitler simulation, which exposes probabilities on the fly, and in a Wikipedia sentiment analysis exploration. Data work shows up in a Jupyter Book cookbook of common data science techniques and a RAGBRAI route prediction algorithm built from past race data. Hardware tinkering is represented by receiver fan automation using a 12V trigger and relay, while a macOS disk space visualizer and a terminal-teaching game collection cover tooling and education.
Because the entries are self-contained experiments, the site is most useful to readers who want to see how a specific problem was approached rather than to find a finished product. Developers, data science learners, and hardware hobbyists can browse by category to find adjacent work, and the mix of write-ups and interactive pages offers both reading and hands-on options.
A sensible way to use the site is to start from a category that matches your interest, then open the linked project or notebook for details. Year labels
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