Showing 16 open source projects for "tiny core linux"

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  • 1
    PlutoUI.jl

    PlutoUI.jl

    A tiny package to make html"input" a bit more Julian

    A tiny package to make HTML "input" a bit more Julian. Use it with the @bind macro in Pluto.
    Downloads: 0 This Week
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  • 2
    Dagger.jl

    Dagger.jl

    A framework for out-of-core and parallel execution

    Dagger.jl is a framework for out-of-core and parallel computing in Julia that allows users to construct and execute dynamic task graphs. It is designed for large-scale, distributed, and memory-efficient computations. Dagger supports lazy evaluation and scheduling across multiple threads or machines, enabling high-performance workflows for data processing, scientific computing, and machine learning.
    Downloads: 0 This Week
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  • 3
    MLJBase.jl

    MLJBase.jl

    Core functionality for the MLJ machine learning framework

    Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ.
    Downloads: 0 This Week
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  • 4
    Vulkan.jl

    Vulkan.jl

    Using Vulkan from Julia

    Vulkan.jl is a lightweight wrapper around the Vulkan graphics and compute library. It exposes abstractions over the underlying C interface, primarily geared toward developers looking for a more natural way to work with Vulkan with minimal overhead. It builds upon the core API provided by VulkanCore.jl. Because Vulkan is originally a C specification, interfacing with it requires some knowledge before correctly being used from Julia. This package acts as an abstraction layer, so that you don't...
    Downloads: 1 This Week
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    Demo Series - Small Business Backup By Veeam

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  • 5
    SciMLBase.jl

    SciMLBase.jl

    The Base interface of the SciML ecosystem

    SciMLBase.jl is the core interface definition of the SciML ecosystem. It is a low-dependency library made to be depended on by the downstream libraries to supply the common interface and allow for the interexchange of mathematical problems. The SciML common interface ties together the numerical solvers of the Julia package ecosystem into a single unified interface. It is designed for maximal efficiency and parallelism, while incorporating essential features for large-scale scientific machine...
    Downloads: 0 This Week
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  • 6
    InMemoryDatasets.jl

    InMemoryDatasets.jl

    Multithreaded package for working with tabular data in Julia

    InMemoryDatasets.jl is a multithreaded package for data manipulation and is designed for Julia 1.6+ (64-bit OS). The core computation engine of the package is a set of customized algorithms developed specifically for columnar tables.
    Downloads: 0 This Week
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  • 7
    AlphaZero.jl

    AlphaZero.jl

    A generic, simple and fast implementation of Deepmind's AlphaZero

    Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...
    Downloads: 8 This Week
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  • 8
    DataFrames.jl

    DataFrames.jl

    In-memory tabular data in Julia

    DataFrames.jl is a powerful Julia package for working with in-memory tabular data. It provides a familiar, flexible, and efficient interface for handling datasets, making it easy to load, manipulate, join, and analyze structured data. With syntax inspired by data frames in R and pandas in Python, it offers intuitive tools while taking advantage of Julia’s speed and type system. The package is actively maintained by the JuliaData community, with contributions from over 200 developers...
    Downloads: 0 This Week
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  • 9
    ChainRulesCore

    ChainRulesCore

    AD-backend agnostic system defining custom forward and reverse rules

    AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system. The ChainRulesCore package provides a light-weight dependency for defining sensitivities for functions in your packages, without you needing to depend on ChainRules itself. This will allow your package to be used with ChainRules.jl, which aims to provide a variety of common...
    Downloads: 0 This Week
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  • 10
    ChainRules.jl

    ChainRules.jl

    Forward and reverse mode automatic differentiation primitives

    The ChainRules package provides a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse--, and mixed-mode primitives. The core logic of ChainRules is implemented in ChainRulesCore.jl. To add ChainRules support to your package, by defining new rules or frules, you only need to depend on the very light-weight package ChainRulesCore.jl. This repository contains ChainRules.jl, which is what people actually use...
    Downloads: 0 This Week
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  • 11
    Metatheory.jl

    Metatheory.jl

    General purpose algebraic metaprogramming

    Metatheory.jl is a general purpose term rewriting, metaprogramming and algebraic computation library for the Julia programming language, designed to take advantage of the powerful reflection capabilities to bridge the gap between symbolic mathematics, abstract interpretation, equational reasoning, optimization, composable compiler transforms, and advanced homoiconic pattern matching features. The core features of Metatheory.jl are a powerful rewrite rule definition language, a vast library...
    Downloads: 0 This Week
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  • 12
    ThinkJulia.jl

    ThinkJulia.jl

    Port of the book Think Python to the Julia programming language

    ThinkJulia.jl is an open source educational project that adapts Think Python by Allen B. Downey into the Julia programming language, with contributions by Ben Lauwens. It provides a comprehensive introduction to programming and computational thinking using Julia’s modern, high-performance features. The book is structured to gradually teach core concepts such as variables, control flow, functions, recursion, object-oriented programming, and data structures, while offering hands-on exercises...
    Downloads: 3 This Week
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  • 13
    DotNET.jl

    DotNET.jl

    This package provides interoperability between Julia and .NET apps

    This package provides interoperability between Julia and Common Language Runtime, the execution engine of .NET applications. Many languages run on CLR, including C#, Visual Basic .NET and PowerShell.
    Downloads: 0 This Week
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  • 14
    Semagrams.jl

    Semagrams.jl

    A graphical editor for graph-like structures

    A graphical editor for graph-like structures based on Catlab. Legacy version built with typescript is in the legacy branch, and will not receive updates; new version with scala is now in the main branch. The core of Semagrams is just a library; in order to make it do things, one needs to create an "app" that uses it. Currently, the only app that is being developed is a Petri net editor, though this will soon change. In order to run the Petri net editor standalone, install Mill and npm, and...
    Downloads: 0 This Week
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  • 15
    ClimateMachine.jl

    ClimateMachine.jl

    Earth System Model that automatically learns from data

    The ClimateMachine is a software package that models the evolution of the Earth system over weeks to centuries. The ClimateMachine solves three-dimensional partial differential equations for the distributions of water, momentum, energy, and tracers such as carbon in the atmosphere, oceans, and on land. The ClimateMachine will harness a wide range of Earth observations and data generated computationally to predict the evolution of Earth’s climate and features such as droughts, rainfall...
    Downloads: 0 This Week
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  • 16
    Diff Zoo

    Diff Zoo

    Differentiation for Hackers

    Diff-zoo is a learning-focused handbook designed to demystify algorithmic differentiation (AD), the core technique powering modern machine learning frameworks. The project introduces AD from a foundational calculus perspective and gradually builds towards toy implementations that resemble systems like PyTorch and TensorFlow. It clarifies the differences and connections between forward mode, reverse mode, symbolic, numeric, tracing, and source transformation approaches to differentiation....
    Downloads: 0 This Week
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