37 projects for "machine learning python" with 2 filters applied:

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  • 1
    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.
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  • 2
    Self-Adapting Large-scale Solver Architecture: system for picking numerical algorithms (linear system solving) based on statistical modeling and machine learning.
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  • 3
    ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.
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  • 4
    Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.
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  • 5
    The Wolfram Machine project is an effort to create a set of documentation and useful modules (both hardware and software) for a computing architecture based on the mathematical theories presented in Steven Wolfram's book _A_New_Kind_of_Science_.
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  • 6
    Software to fit whole-sentence language models using the principle of maximum entropy. For developers of speech recognizers, text prediction interfaces, OCR, machine translation software.
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  • 7
    CompLearn is a general-purpose compression-based machine learning system that uses data compression to learn or data mine patterns in arbitrary data.
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  • 8
    FLPD is an automatic learning system based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.
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  • 9
    Ruby SVM is a Ruby binding to the very popular and highly useful libsvm library (released under a seperate license) This allows you to effortlessly experiment with machine learning, in particular Support Vector Machines, in Ruby. SVM's have found use in
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  • 10
    Emily is a friendly name for the Machine Learning Environment (MLE). This project is at an early stage of development, and no alpha code is yet available.
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  • 11
    Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
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  • 12
    The ROSETTA C++ library is a collection of C++ classes and routines that enable discernibility-based empirical modelling and data mining. Comprises useful routines for machine learning in general and for rough set theory in particular.
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