作为一Julia学习新人，想做人工智能方向，不知道有一条战线的盟友么？
就简单罗列一下各个相关领域里有代表性的工具箱吧，这些包都有对应的文档和教程，当然都是英文的。需要注意的是：目前的Julia生态对调包侠并不友好，需要有一定的理论支撑才好做点什么东西
自动微分：GitHub - FluxML/Zygote.jl: 21st century AD
深度学习：GitHub - FluxML/Flux.jl: Relax! Flux is the ML library that doesn't make you tensor
概率模型：GitHub - TuringLang/Turing.jl: Bayesian inference with probabilistic programming.
优化模型：GitHub - jump-dev/JuMP.jl: Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
微分方程：GitHub - 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.
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