Author: princejohnsite

In the last blog, we explored how Bayesian Non-Parametrics (BNP) allows us to model data without fixing the number of clusters or parameters in advance. But how does that actually work? Let’s break down one of the most elegant ideas in BNP: the Chinese Restaurant Process (CRP) — a metaphor that turns infinite possibilities into a beautifully simple process. 🏮 What…

Imagine trying to fit a square peg in a round hole. That’s often what traditional statistical models do — they assume the data follows a specific shape or distribution (like a normal curve), even when reality is much messier. Bayesian Non-Parametrics (BNP) offers an elegant solution: don’t assume a fixed shape. Let the data speak for itself.…