Julia: Introductions and Philosophy:
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Julia References:
- The Julia Language - home download Julia here
- Julia Documentation
- Julia Cheatsheet - The Fast Track to Julia
- MATLAB-Julia-Python Cheatsheet - quantecon.org
- Julia Data Science eBook - 2021, pdf, 168 pages
- Julia Unicode Characters - for backslash tab completion
- Named Colors in Julia
- Julia Packages
(roughly in order used in MIT Computational Thinking & Udemy Zero to Expert courses.)
(* recommended packages to add via package manager when starting a new project, ymmv) :
- JuliaPackages.com - bills itself as a "one-stop-shop"
- InteractiveUtils - loaded automatically in "interactive mode" i.e. CLI
- Command Line (CLI) Options
- -------------------------------------------------------------
- *Pluto The "User Notebook" (see main Pluto topic below)
- *PlutoUI i.e. "User Interface" (see main Pluto topic below)
- --------------------------Plots-------------------------------
- *Plots - at JuliaPlots.org
- Plotly - (cloud)
- *PlotlyJS - (local) a visualization library
- MakiePlots
- LightGraphs
- GraphPlot
- RecipesBase
- GraphRecipes
- -------------------------Images------------------------------
- ImageMagick
- ImageFiltering - blur, sharp, etc., plus non-linear filters
- ImageIO
- ImageShow
- Colors
- ColorVectorSpace
- ColorSchemes
- Images - example: show Mandlebrot set using CPU, ref.: doggydot video
- ------------------------Utilities------------------------------
- DelimitedFiles - standard library, reading files inc. csv files
- FileIO
- HypertextLiteral
- LaTeXStrings
- BenchmarkTools
- Pringf - standard library, print formatting
- Underscores
- WebIO
- WAV - read/write WAV audio files
- CUDA - main interface for working with NVIDIA CUDA GPUs using Julia.
- -----------------------Linear Algebra--------------------------
- Standard Linear Algebra Library
- LinearAlgebra
- Built-in Matrix Factorizations (decompositions) - list
- OffsetArrays - change indices
- StaticArrays
- MappedArrays
- Sparse Matrices:
- GLM - linear models and generalized linear models
- -----------------------Data--------------------------
- *DataFrames - documentation
- CSV
- Tables
- BrowseTables inc. HTMLTable() useful in Pluto
- Arrow - Apache Arrow Home Page - in-memory data processing
- VegaLite - plot package, stat plots
(implementation of Vega = visualization grammar - Vega home ~ VegaLite home) Vega-Lite supports both data transformations (e.g., aggregation, binning, filtering, sorting) and visual transformations (e.g., stacking and faceting). VegaLite Video
- VegaDatasets - loads example datasets used by Vega
- Clustering
- RDatasets - add datasets used in R programming language
- ----------------------Statistics------------ ---------------
- Statistics
- Distributions
- StatsBase
- *StatsPlots
- Combinatorics
- HypothesisTests
- Rmath - emulates R's d-p-q-r functions for probability distributions
- ------------------------Math - General--------------------------------
- Random - standard Julia library for random number generation
- Symbolics - doggo video
- Calculus
- ForwardDiff
- DifferentialEquations - tutorial ~ (also see SciML in Machine Learning)
- ModelingToolkit - ODE modeling tutorial
- Unitful
- NonlinearSolve
- SpecialFunctions - inc. Bessel, exp, trig., Airy, gamma...
- Roots - roots of continuous scalar functions of a single real variable
- Optimization:
- FFT Related:
- FFTW - fast Fourier transform
- DSP - digital signal processing
- ------------------------Climate Modeling-----------------
- ClimateMARGO
- ----------------------Machine Learning------------ ---------------
- DifferentialEquations.jl: SciML
Scientific Machine Learning Enabled Simulation and Estimation
- MLBase - machine learning utilities
- DecisionTree - DecisionTree (CART) and Random Forest algorithms
- LIBSVM - Support Vector Machine models
- Flux
- ------------------------Nonlinear Dynamics-----------------
- JuliaDynamics
- Agents.jl - framework for agent-based modeling (ABM)
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Pluto:
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Julia at MIT:
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Julia Videos:
- "Why Julia?" - A high level description of features/benefits of Julia
by Tim Holy Oct 5, 2021
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MATH2021 HKUST Linear Algebra Course With Julia:
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Linear Algebra - Quantitative Economics with Julia :
by Jesse Perla & Thomas J. Sargent & John Stachurski
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Fundamantala of Numerical Computing:
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Julia Projects and Examples:
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