Chapter 03 · Section III · 14 min read
Naive Bayes classification
A genuinely useful AI technique that fits on one whiteboard — and powered spam filters for two decades.
Naive Bayes is the simplest practical AI classifier. It applies Bayes’ rule under an obviously-wrong assumption: that each piece of evidence is independent of the others. Surprisingly, this assumption — naive as it is — works well enough to filter spam, classify documents, and triage support tickets.
It is also a perfect first model. You can implement it in twenty lines of Python. You can explain it to a regulator. You can audit it. Most “AI” deployments in 2026 would be better served by Naive Bayes than by a large language model — but it is harder to put in a press release.
This section is a stub. The full version will walk through training a Naive Bayes filter on Nepali SMS spam.