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Hipo is a hypothetical computer to facilitate the learning of machine language. The student can use hipo to develop simple programs and understand the internal logic of a computer. There is a plan to implement Donald Knuth's MMIX machine language, also.
Dinaao Is Not An Apple One Emulator.
It does however already run most apple1 software. It runs on the command line so cut and paste works perfectly. A great 65C02/Basic learning/development environment.
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A Java-written MIPS simulator developed to stimulate people learning the Assembly language. It adds graphics, sounds and user interation to make writing assembly programs more interesting.
Machinelearning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).
Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machinelearning problems and a specific set of models for gene prediction using semi-Markov CRFs.
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machinelearning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machinelearning. The code is well documented and easy to extend, especially for adding new weak learners.
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Cigol (logic, spelled backwards) is a deductive logic solver. It can be embedded inside a parent program or used from the command line. It has absolutely no relationship to Tom Mitchell's book on MachineLearning.
GenP Genetic Programming Library is a cross-platform library of genetic programming functions for generic application. Initially it's purpose is for machinelearning in board games but should be applicable to any purpose.
DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machinelearning algorithms.
It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure.
It can handle highly non-linear dependencies between multivariate random variables.
Weka++ is a collection of machinelearning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.