Showing 183 open source projects for "artificial"

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  • 1
    The Python Genetic Programming Project implements a Genetic Programming System a la J Koza in Python.
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  • 2
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
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  • 3
    Project to Design and Implement a new programming language. The language is named Hybrid (c), as it's nature. We "build on" existing languages (Python & others), and not start from scratch (as C++ builds on C). see Docs.
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  • 4
    Cellicone is a project to develop an artificial life organism with the necessary components to make it comparable to biological life as we know it. This includes components ranging from proteins to cells to organs to limbs, and many steps between.
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  • 5
    aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
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  • 6
    a distributed engine for abstract neural network development via natural-language programming
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  • 7
    nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.
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  • 8
    ExoPlanet

    ExoPlanet

    GUI based toolkit for running common Machine Learning algorithms.

    ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve,...
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