Search Results for "spreadsheet machine learning" - Page 80

Showing 2009 open source projects for "spreadsheet machine learning"

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  • 1
    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 Machine Learning.
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  • 2
    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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  • 3
    An open-source Perl framework for automatic text categorization using Machine Learning methods.
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  • 4

    Betelgeuse

    Powerful machine learning modeling software suitable for industry use.

    Betelgeuse is a machine learning modeling package designed to meet the requirements of heavy-duty industry use. It was designed to be efficient, reliable, and highly modular; it is developed primarily in Python to promote maintainability and rapid development, but uses Cython and C in critical bottlenecks for efficiency. It focuses on high-quality implementations of a diverse set of the most widely used machine learning algorithms.
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  • 5
    Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.
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  • 6
    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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  • 7
    ITAS puts a human user in the place of a Robocup agent by providing a visual display of the agent's environment and an interface for controlling the agent. It also generates a log of the user's environment and actions for use in machine learning.
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  • 8
    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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  • 9
    ApMl provides users with the ability to crawl the web and download pages to their computer in a directory structure suitable for a Machine Learning system to both train itself and classify new documents. Classification Algorithms include Naive Bayes, KNN
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  • 10
    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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  • 11
    A Java library for developing board games with a focus on experimenting with different types of machine learning.
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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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  • 13
    GenP Genetic Programming Library is a cross-platform library of genetic programming functions for generic application. Initially it's purpose is for machine learning in board games but should be applicable to any purpose.
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  • 14
    A scientific framework for testing and learning the learning of a computer.
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  • 15
    Compiler and virtual machine of a new programming language similar to pascal with learning proposals for computer science engineering students.
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  • 16

    AraRooter

    Find Arabic Root Word

    Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy.
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  • 17
    lstm network library
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  • 18
    UnBFuzzy is an API for fuzzy-logic and learning algorithms for fuzzy systems.
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  • 19
    Spec is a voice control based on the libraries of Sphinx-4.
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  • 20

    GENet

    A genetic algorithm framework for artificial neural networks.

    A genetic algorithm framework to allow the evolution of synapse weights and topologies of artificial neural networks.
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  • 21
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection - https://github.com/Tessellate-Imaging/Monk_Object_Detection. ...
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  • 22
    qMaZda

    qMaZda

    Image analysis software

    The open source project to port image analysis MaZda program to Linux and OS X platforms. See: http://www.eletel.p.lodz.pl/programy/mazda/
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  • 23
    The goal of the project it to learn how to use Neural Networks, and teach one how to play tic tac toe, and get to the never losing ability that most people can play at.
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  • 24

    Cinefile

    A category-based approach to exploring film data.

    Cinefile is a prototype of a category-based method of database exploration. It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories. Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the...
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  • 25

    Supertagger

    Software for assigning supertags.

    Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.
    Downloads: 0 This Week
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