R package for simulating, estimating, and modeling with Markov chains
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Updated
Apr 17, 2022 - R
R package for simulating, estimating, and modeling with Markov chains
This is a collection of scripts and functions that serve as exercises for understanding and writing various numerical methods from scratch.
Exercises and experiments with Bayesian statistics and markov chains.
Section 14 of a tentative book on Markov chains with detailed analysis of eigenvalues of Markov chains of random walks.
Section 12 of a tentative book on Markov chains with examples of application of Gibbs sampling
Creating a Twitter Bot using Dan Shiffman's tutorial and scraped data from NYUAD Confessions and C&C using BS4 and Selenium Webdriver. Fed the results into an RNN model to generate "confessions"
Section 2 of tentative book on theory and examples of Markov Chains
Generate words using markov chains
Numerical Methods I, CS 357, Univ. of Illinois
Section 11 of tentative book on Markov chains, with application of Monte Carlo Markov chain methods to the Ising model, image reconstruction with Gibbs sampling, and Bayesian hierarchical statistical models.
Auto generate tweets powered by pre-trained GPT2 based large language model (LLM) available offline.
Sample Python Program, trained using Markov Chains to generate random sentences based on start word
Section 3 of a tentative book on theory and examples of Markov Chains
Simple generative writing with Markov chains
Perl module to learn a corpus and make predictions using a multi-order (multi-dimensional) Markov learner
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