Probability

Markov Chain Basic is an exploratory NLP project that uses Markov transitions to generate text and study long-run behavior in probabilistic sequence models. Highlights Builds transition maps from input corpora. Generates synthetic text using stochastic state transitions. Serves as an intuition-first bridge into probabilistic NLP.

This publication explains Markov chains with an intuition-first approach and practical examples for state-transition thinking. Publication link: Read on Medium