Showing 6 open source projects for "documentation"

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  • 1
    Turing.jl

    Turing.jl

    Bayesian inference with probabilistic programming

    Bayesian inference with probabilistic programming.
    Downloads: 7 This Week
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  • 2
    Zygote

    Zygote

    21st century AD

    Zygote provides source-to-source automatic differentiation (AD) in Julia, and is the next-gen AD system for the Flux differentiable programming framework. For more details and benchmarks of Zygote's technique, see our paper. You may want to check out Flux for more interesting examples of Zygote usage; the documentation here focuses on internals and advanced AD usage.
    Downloads: 1 This Week
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  • 3
    MLJ.jl

    MLJ.jl

    A Julia machine learning framework

    MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization.
    Downloads: 0 This Week
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  • 4
    Model Zoo

    Model Zoo

    Please do not feed the models

    FluxML Model Zoo is a collection of demonstration models built with the Flux machine learning library in Julia. The repository provides ready-to-run implementations across multiple domains, including computer vision, natural language processing, and reinforcement learning. Each model is organized into its own project folder with pinned package versions, ensuring reproducibility and stability. The examples serve both as educational tools for learning Flux and as practical starting points for...
    Downloads: 1 This Week
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  • 5
    BetaML.jl

    BetaML.jl

    Beta Machine Learning Toolkit

    The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its...
    Downloads: 0 This Week
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  • 6
    FEniCS.jl

    FEniCS.jl

    A scientific machine learning (SciML) wrapper for the FEniCS

    FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts. Installation and direct access to FEniCS via a Conda installation. Alternatively one may use their current FEniCS installation. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their...
    Downloads: 0 This Week
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