Dependency Packages
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Flux.jl4466Relax! Flux is the ML library that doesn't make you tensor
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DifferentialEquations.jl2841Multi-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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JuMP.jl2210Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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Turing.jl2026Bayesian inference with probabilistic programming.
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Plots.jl1825Powerful convenience for Julia visualizations and data analysis
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Gen.jl1791A general-purpose probabilistic programming system with programmable inference
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MLJ.jl1779A Julia machine learning framework
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Zygote.jl147621st century AD
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UnicodePlots.jl1421Unicode-based scientific plotting for working in the terminal
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ModelingToolkit.jl1410An 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
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Symbolics.jl1353Symbolic programming for the next generation of numerical software
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AlphaZero.jl1232A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
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Optim.jl1116Optimization functions for Julia
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NeuralPDE.jl966Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
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NeuralNetDiffEq.jl966Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
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Oceananigans.jl962🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
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ForwardDiff.jl888Forward Mode Automatic Differentiation for Julia
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DSGE.jl864Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
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DiffEqFlux.jl861Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
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DynamicalSystems.jl834Award winning software library for nonlinear dynamics and nonlinear timeseries analysis
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OnlineStats.jl831⚡ Single-pass algorithms for statistics
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Javis.jl827Julia Animations and Visualizations
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JuliaDB.jl766Parallel analytical database in pure Julia
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LoopVectorization.jl742Macro(s) for vectorizing loops.
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Agents.jl728Agent-based modeling framework in Julia
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SciMLTutorials.jl713Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
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DiffEqTutorials.jl713Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
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Optimization.jl712Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
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GalacticOptim.jl712Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
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Gridap.jl691Grid-based approximation of partial differential equations in Julia
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Dagger.jl630A framework for out-of-core and parallel execution
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WaterLily.jl616Fast and simple fluid simulator in Julia
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Tullio.jl605⅀
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FastAI.jl589Repository of best practices for deep learning in Julia, inspired by fastai
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Luxor.jl586Simple drawings using vector graphics; Cairo "for tourists!"
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SymbolicRegression.jl580Distributed High-Performance Symbolic Regression in Julia
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Convex.jl564A Julia package for disciplined convex programming
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SymbolicUtils.jl537Symbolic expressions, rewriting and simplification
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ApproxFun.jl537Julia package for function approximation
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OrdinaryDiffEq.jl533High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
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