Dependency Packages
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GeometryBasics.jl164Basic Geometry Types
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Accessors.jl175Update immutable data
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IterTools.jl152Common functional iterator patterns
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Contour.jl44Calculating contour curves for 2D scalar fields in Julia
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PrettyTables.jl403Print data in formatted tables.
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TranscodingStreams.jl85Simple, consistent interfaces for any codec.
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Roots.jl342Root finding functions for Julia
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MLFlowClient.jl46Julia client for MLFlow.
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Plots.jl1825Powerful convenience for Julia visualizations and data analysis
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ConstructionBase.jl34Primitives for construction of objects
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CUDA.jl1193CUDA programming in Julia.
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JLD2.jl549HDF5-compatible file format in pure Julia
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ChainRulesCore.jl253AD-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.
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ForwardDiff.jl888Forward Mode Automatic Differentiation for Julia
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ChainRules.jl435Forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
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Latexify.jl558Convert julia objects to LaTeX equations, arrays or other environments.
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DataStructures.jl690Julia implementation of Data structures
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DataFrames.jl1725In-memory tabular data in Julia
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HypothesisTests.jl296Hypothesis tests for Julia
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Reexport.jl162Julia macro for re-exporting one module from another
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LLVM.jl130Julia wrapper for the LLVM C API
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TimerOutputs.jl651Formatted output of timed sections in Julia
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IterativeSolvers.jl401Iterative algorithms for solving linear systems, eigensystems, and singular value problems
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MLStyle.jl402Julia functional programming infrastructures and metaprogramming facilities
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PackageCompiler.jl1415Compile your Julia Package
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Zygote.jl147621st century AD
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StatsFuns.jl232Mathematical functions related to statistics.
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KernelAbstractions.jl363Heterogeneous programming in Julia
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Term.jl439Julia library for stylized terminal output
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AbstractTrees.jl200Abstract julia interfaces for working with trees
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LinearMaps.jl303A Julia package for defining and working with linear maps, also known as linear transformations or linear operators acting on vectors. The only requirement for a LinearMap is that it can act on a vector (by multiplication) efficiently.
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Optim.jl1116Optimization functions for Julia
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MLJ.jl1779A Julia machine learning framework
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StatsBase.jl584Basic statistics for Julia
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MathOptInterface.jl388A data structure for mathematical optimization problems
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CommonSolve.jl19A common solve function for scientific machine learning (SciML) and beyond
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Format.jl37A Julia package to provide C and Python-like formatting support
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InvertedIndices.jl81A simple index type that allows for inverted selections
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ColorSchemes.jl187Colorschemes, colormaps, gradients, and palettes
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FixedPointNumbers.jl79Fixed point types for julia
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