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.