There are 11 repositories under markov-chain topic.
Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog
An automated subreddit with posts created using markov chains
Curso de Álgebra Lineal
:black_nib: Markov process-based procedural name and word generator demo
The Minimal LZMA (minlzma) project aims to provide a minimalistic, cross-platform, highly commented, standards-compliant C library (minlzlib) for decompressing LZMA2-encapsulated compressed data in LZMA format within an XZ container, as can be generated with Python 3.6, 7-zip, and xzutils
Generate passwords with Alfred
Types and utility functions for summarizing Markov chain Monte Carlo simulations
Toolbox full of Algorithmic Composition methods
Code for "A-NICE-MC: Adversarial Training for MCMC"
A Modern Probabilistic Model Checker
Markov Chain Twitter Bot generator
An open source soccer/football manager game
Twitch Bot for generating messages based on what it learned from chat
Easy Handling Discrete Time Markov Chains
An endless version of Erik Satie's Gnossiennes No. 1
A Java implementation of various procedural name generation algorithms, including combinatorial, consonant vowel, context-free grammar, and Markov chain.
Statistical analysis and visualization of state transition phenomena
Code for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)
A library for discrete-time Markov chains analysis.
A Markov chain Discord chat bot. Generates unique messages by learning from past messages. Also occasionally attaches images to messages.
Reinforcement learning (RL) implementation of imperfect information game Mahjong using markov decision processes to predict future game states
A Reddit bot that generates new context-aware comments using Markov chains trained from a set of given users or subreddits comments history.
Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Supervised training supported. Easily extendable with other types of probablistic models.