Markov Libraries

7 Components & Libraries

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Markov Libraries

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 4MB of noise : Generate 4MB of whitespace: Generate 4MB of noise: Generate 4MB of whitespace: If you use WSL, ... For Linux native builds, ... The author would like to thank the shoulders of…

An open source soccer/football manager game

The purpose of this project is to provide an interesting and fun game for simulating a manager's life in a simple way: managing a team, dealing with players, finances and many other features. Resembl…

ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.

ParaMonte has been developed while bearing the following design goals in mind: The ParaMonte library relies on three independent parallelism paradigms for parallel applications: The ParaMonte librari…

Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.

Sequentia is a Python package that provides various classification and regression algorithms for sequential data, including methods based on hidden Markov models and dynamic time warping. Some exam…

Monte Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree accordingly. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games and planning problems. In this project I used a board game called "HEX" as a platform to test different simulation strategies in MCTS field.

MONTE Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree according to the results. It has a…

Markov Chain Twitter Bot generator

Dankenstein is a Markov Chain Twitter Bot generator, based on making a mashup of different corpora. The software itself is implemented using Bash, Make, and Python. You'll need a Twitter Account and …

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMEN…