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Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University. The source code for the entire course material is open and everyone is cordially invited to use it for self-learning (students) or to set up their own course (lecturers).
Java Modelling Tools is a suite of scientific tools for performance analysis and modelling using queueing theory and colored stochastic Petri nets. Models are solved either with analytical, asymptotic or simulation methods; workload characterization tools are also included in the suite.
See the project website for more details: http://jmt.sf.net
The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects.
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Trofast is an intelligent spell checker library based on statistical analysis developed for the Danish language. It makes use of n-grams, hidden Markov models and the Viterbi-algorithm.