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This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
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Belkerda is a simple Python AI program that takes a user's input, builds a log of random numbers, picks a random entry, and displays it. If it is correct, then it reenters that number back into the log several times, overwriting the original, random numbers. If it is not, however, it overwrites a lower amount of entries.
The Movinator is a movie database application. It manages information about movies plus ratings assigned to movies by movie critics. Based on these ratings and user ratings, the application can also make movie recommendations.
Open Metaheuristic (oMetah) is a library aimed at the conception and the rigourous testing of metaheuristics (i.e. genetic algorithms, simulated annealing, ...). The code design is separated in components : algorithms, problems and a test report generator
Modules for developing, configuring and running a computation based on function blocks entirely in Python. Function block based computation is a data, event and state driven approach to data processing.
This is a python implementation that handles floating points correctly,there are still some bugs but I'm working on it . The point was to work around some stuff that made no sense for floats,like 0.1+0.2 == 0.3 is false.
TiVo style recommendation engine for MythTV. MythMagic selects and automatically records shows from your program guide based on previous viewing habits. Recordings can be accepted or rejected to improve recommendation accuracy.
ngram is a module to compute the similarity between two strings. It is different to python's "difflib.SequenceMatcher" in that it cares more about the size of both strings. ngram is an port and extension of the perl module called "String::Trigram
Based on the introduction of Genetic Algorithms in the excellent book "Collective Intelligence" I have put together some python classes to extend the original concepts.
This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
A C++ RAII ( Resource Allocation Is Initialization ) implementation of an automatic pointer/reference. Pointable/Referenced objects are handled in a manner similar to Python. Strives to have the simplest syntax possible.
HDRFlow is a framework to process high-dynamic range (HDR) and RAW images. It's written in C++, and is both cross-platform and hardware accelerated on modern GPUs.
This small C package is made of an independent AVL tree library, and of an extension module for Python that builds upon it to provide objects of type 'avl_tree' in Python, which can behave as sorted containers or sequential lists.
A threaded Web graph (Power law random graph) generator written in Python. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine. It implements a threaded variant of the RMAT algorithm.
Ropes are a scalable string implementation that are designed for efficient operation by utilizing lazy operations such as concatenation and slicing. This is a python C module which implements ropes for pythons.
compactpath is a python package to handle compacting of filepaths. compacting of filepaths may be useful in gui programming where filepaths of arbitrary lenght have to be displayed in widgets with limited visual space.
The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.