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  • 1
    Mixed-effects models in Julia

    Mixed-effects models in Julia

    A Julia package for fitting (statistical) mixed-effects models

    ...If the potential levels of the covariate are fixed and reproducible, e.g. the levels for Sex could be "F" and "M", they are modeled with fixed-effects parameters. If the levels constitute a sample from a population, e.g. the Subject or the Item at a particular observation, they are modeled as random effects.
    Downloads: 3 This Week
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  • 2
    DynamicalBilliards.jl

    DynamicalBilliards.jl

    An easy-to-use, modular, extendable and absurdly fast Julia package

    A Julia package for dynamical billiard systems in two dimensions. The goals of the package is to provide a flexible and intuitive framework for fast implementation of billiard systems of arbitrary construction.
    Downloads: 0 This Week
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  • 3
    Bootstrap.jl

    Bootstrap.jl

    Statistical bootstrapping library for Julia

    Bootstrapping is a widely applicable technique for statistical estimation.
    Downloads: 0 This Week
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  • 4
    Augmentor.jl

    Augmentor.jl

    A fast image augmentation library in Julia for machine learning

    ...It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a sequence of operations for which the parameters can (but need not) be random variables, as the following code snippet demonstrates.
    Downloads: 0 This Week
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  • Total Network Visibility for Network Engineers and IT Managers Icon
    Total Network Visibility for Network Engineers and IT Managers

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