: Julia is a high-level, high-performance dynamic language for technical computing. [ julialang.org/](https://julialang.org/). 38 | 39 | - [Julia Documentation](https://docs.julialang.org/en/v1/) : Welcome to the documentation for Julia. 40 | 41 | 42 | - ### Awesome List 43 | 44 | - [greister/Awesome-Julia](https://github.com/greister/Awesome-Julia)

: A curated list of awesome julia libraries, softwares and tutorials. 45 | 46 | - [old-julia-codes/awesomeJulia](https://github.com/old-julia-codes/awesomeJulia)

: awesome Julia. 47 | 48 | - [widged/awesome-julia-datasciences](https://github.com/widged/awesome-julia-datasciences)

: Resources about Julia for DataSciences / Machine Learning. 49 | 50 | 51 | 52 | - ### Community 53 | 54 | - [JuliaCN](https://github.com/JuliaCN) : [Julia 中文社区](https://cn.julialang.org/)。社区驱动，致力于 Julia 编程语言中文支持的开源组织。 55 | 56 | 57 | - ### Learning Resources 58 | 59 | - [Julia Documentation](https://docs.julialang.org/en/v1/) : Welcome to the documentation for Julia. 60 | 61 | - [JuliaCN/JuliaZH.jl](https://github.com/JuliaCN/JuliaZH.jl)

: Julia语言中文文档。[docs.juliacn.com](https://docs.juliacn.com/latest/) 62 | 63 | - [JuliaCN/JuliaDataScience](https://github.com/JuliaCN/JuliaDataScience)

: Julia Data Science 中文版。[cn.julialang.org/JuliaDataScience/](https://cn.julialang.org/JuliaDataScience/) 64 | 65 | 66 | 67 | 68 | ## Data Structure and Algorithm 69 | 70 | - [TheAlgorithms/Julia](https://github.com/TheAlgorithms/Julia)

: Algorithms implemented in Julia (for educational purposes). 71 | 72 | - [mossr/BeautifulAlgorithms.jl](https://github.com/mossr/BeautifulAlgorithms.jl)

: Concise and beautiful algorithms written in Julia. 73 | 74 | 75 | 76 | ## Package Manager 77 | 78 | - [JuliaCN/Julia2Nix.jl](https://github.com/JuliaCN/Julia2Nix.jl)

: The Nix interface to Julia Ecosystem [maintainer=@GTrunSec]. [cn.julialang.org/Julia2Nix.jl/](http://cn.julialang.org/Julia2Nix.jl/). 79 | 80 | 81 | 82 | 83 | 84 | ## FFI Bindings 85 | 86 | - [PyCall](https://github.com/JuliaPy/PyCall.jl)

: Calling Python functions from the Julia language. 87 | 88 | - [jlrs](https://github.com/Taaitaaiger/jlrs)

: Julia bindings for Rust. 89 | 90 | 91 | 92 | 93 | 94 | ## GPU Computing 95 | 96 | - [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl)

: CUDA programming in Julia. [juliagpu.org/](https://juliagpu.org/) 97 | 98 | - [AMDGPU.jl](https://github.com/JuliaGPU/AMDGPU.jl)

: AMD GPU (ROCm) programming in Julia. 99 | 100 | 101 | 102 | 103 | ## Scientific Computation 104 | 105 | - ### Numerical Calculation 106 | 107 | - [DifferentialEquations.jl](https://github.com/SciML/DifferentialEquations.jl)

: Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia. [docs.sciml.ai/DiffEqDocs/stable/](https://github.com/SciML/DifferentialEquations.jl) 108 | 109 | - [ModelingToolkit.jl](https://github.com/SciML/ModelingToolkit.jl)

: An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations. [mtk.sciml.ai/dev/](https://docs.sciml.ai/ModelingToolkit/dev/) 110 | 111 | 112 | 113 | 114 | 115 | - ### Linear Algebra 116 | 117 | - [GenericLinearAlgebra.jl](https://github.com/JuliaLinearAlgebra/GenericLinearAlgebra.jl)

: Generic numerical linear algebra in Julia. 118 | 119 | - [JuliaArrays/LazyArrays.jl](https://github.com/JuliaArrays/LazyArrays.jl)

: Lazy arrays and linear algebra in Julia. 120 | 121 | 122 | 123 | 124 | 125 | - ### Optimization Engine 126 | 127 | - [JuMP](https://github.com/jump-dev/JuMP.jl)

: Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear). [jump.dev/](https://jump.dev/) 128 | 129 | - [EAGO](https://github.com/PSORLab/EAGO.jl)

: EAGO: Easy-Advanced Global Optimization. EAGO is an open-source development environment for robust and global optimization in Julia. 130 | 131 | 132 | 133 | 134 | 135 | - ### Data Analysis and Visualization 136 | 137 | - [Makie.jl](https://github.com/MakieOrg/Makie.jl)

: Visualizations and plotting in Julia. [docs.makie.org/stable](https://docs.makie.org/stable/) 138 | 139 | - [Plots.jl](https://github.com/JuliaPlots/Plots.jl)

: Powerful convenience for Julia visualizations and data analysis. [docs.juliaplots.org](https://docs.juliaplots.org/stable/) 140 | 141 | - [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl)

: In-memory tabular data in Julia. [dataframes.juliadata.org/stable/](https://dataframes.juliadata.org/stable/) 142 | 143 | 144 | 145 | 146 | 147 | 148 | ## Machine Learning 149 | 150 | - ### Machine Learning Framework 151 | 152 | 153 | - [Flux](https://github.com/FluxML/Flux.jl)

: Relax! Flux is the ML library that doesn't make you tensor. [fluxml.ai/](https://fluxml.ai/) 154 | 155 | - [MLJ](https://github.com/alan-turing-institute/MLJ.jl)

: A Machine Learning Framework for Julia. 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](https://alan-turing-institute.github.io/MLJ.jl/dev/model_browser/#Model-Browser) written in Julia and other languages. 156 | 157 | - [ITensor](https://github.com/ITensor/ITensors.jl)

: A Julia library for efficient tensor computations and tensor network calculations. [itensor.org](https://itensor.org/) 158 | 159 | - [TensorOperations.jl](https://github.com/Jutho/TensorOperations.jl)

: Julia package for tensor contractions and related operations. [jutho.github.io/TensorOperations.jl/stable/](about:blank) 160 | 161 | - [TensorKit.jl](https://github.com/Jutho/TensorKit.jl)

: A Julia package for large-scale tensor computations, with a hint of category theory. 162 | 163 | 164 | 165 | 166 | - ### Object Detection 167 | 168 | - [ObjectDetector.jl](https://github.com/r3tex/ObjectDetector.jl)

: Pure Julia implementations of single-pass object detection neural networks. 169 | 170 | - [AndreyGermanov/yolov8_onnx_julia](https://github.com/AndreyGermanov/yolov8_onnx_julia)

: YOLOv8 inference using Julia. 171 | 172 | - [IanButterworth/YOLO.jl](https://github.com/IanButterworth/YOLO.jl)

: YOLO Object Detection in Julia. 173 | 174 | 175 | 176 | 177 | 178 | ## Image and Video Processing 179 | 180 | - [JuliaImages/Images.jl](https://github.com/JuliaImages/Images.jl)

: An image library for Julia. [juliaimages.org/](https://juliaimages.org/latest/) 181 | 182 | - [JuliaImages/OpenCV.jl](https://github.com/JuliaImages/OpenCV.jl)

: Use OpenCV in Julia!! 🚀. [juliaimages.org/OpenCV.jl/dev/](https://juliaimages.org/OpenCV.jl/dev/) 183 | 184 | 185 | 186 | ## Web Framework 187 | 188 | - [Genie.jl](https://github.com/GenieFramework/Genie.jl)

: 🧞The highly productive Julia web framework. [genieframework.com](https://genieframework.com/) 189 | 190 | 191 | 192 | 193 | ## Performance Benchmark 194 | 195 | - [mdmaas/julia-numpy-fortran-test](https://github.com/mdmaas/julia-numpy-fortran-test)

: Comparing Julia vs Numpy vs Fortran for performance and code simplicity. 196 | 197 | 198 | 199 | 200 | ## GUI 201 | 202 | - [JuliaGizmos/Blink.jl](https://github.com/JuliaGizmos/Blink.jl)

: Web-based GUIs for Julia. 203 | 204 | 205 | 206 | ## Blogs 207 | 208 | - [MatecDev](https://www.matecdev.com/) 209 | - [2021-09-20，Testing Julia: Fast as Fortran, Versatile as Python](https://www.matecdev.com/posts/numpy-julia-fortran.html) 210 | - [2022-01-17，Julia vs Numba and Cython: Looking Beyond Microbenchmarks](https://www.matecdev.com/posts/julia-python-numba-cython.html) 211 | - [2023-06-02，Julia: 17X Faster than Python's Scipy, and Easier Too!](https://www.matecdev.com/posts/julia-17x-faster-vs-python-scipy.html) --------------------------------------------------------------------------------