Showing 5 open source projects for "deep learning with python"

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  • 1
    dlib

    dlib

    Toolkit for making machine learning and data analysis applications

    Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about...
    Downloads: 5 This Week
    Last Update:
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  • 2
    XGBoost

    XGBoost

    Scalable and Flexible Gradient Boosting

    XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost...
    Downloads: 5 This Week
    Last Update:
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  • 3
    SMILI

    SMILI

    Scientific Visualisation Made Easy

    The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with...
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    Downloads: 8 This Week
    Last Update:
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  • 4
    Uranie

    Uranie

    Uranie is CEA's uncertainty analysis platform, based on ROOT

    Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available...
    Downloads: 3 This Week
    Last Update:
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  • 5
    Inviwo

    Inviwo

    Interactive Visualization Workshop

    ... learning models. The platform supports both novice users through its graphical interface and advanced users through scripting and plugin development.
    Downloads: 0 This Week
    Last Update:
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