From 3a699ea1af5cb15951d7e113cee93d37fe4d88f2 Mon Sep 17 00:00:00 2001 From: tndoan Date: Mon, 7 Dec 2020 18:51:24 -0500 Subject: [PATCH] update readme file --- README.md | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 5fdfa16..0581cd2 100644 --- a/README.md +++ b/README.md @@ -1 +1,16 @@ -# ISL \ No newline at end of file +# ISL + +## Introduction +[An Introduction to Statistical Learning: With Applications in R](http://faculty.marshall.usc.edu/gareth-james/ISL/) is a great book to learn data science. However, the associated code is [R](https://www.r-project.org/about.html) which is a nice programming language for statisticians. There is a project named [ISLR-python](https://github.com/JWarmenhoven/ISLR-python) which ports the book to Python. I was inspired by the Python project and try to implement the introduced materials in this book to [Julialang](https://julialang.org/). Julia is a new language which is faster than C and more friendly to scientific computing than Python. + +## Library + +In this project, I use Julia v1.5.1 and the following library +- [Plots.jl](https://github.com/JuliaPlots/PlotDocs.jl) for visualization +- [CSV.jl](https://csv.juliadata.org/v0.4.0/) for reading csv file +- [Clustering.jl](https://github.com/JuliaStats/Clustering.jl) for clustering algorithms +- [LIBSVM.jl](https://github.com/JuliaML/LIBSVM.jl) for LibSVM implementation +- [StatsPlots.jl](https://github.com/JuliaPlots/StatsPlots.jl) for plotting statistic +- [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) for data frame +- [GLM.jl](https://github.com/JuliaStats/GLM.jl) for generalized linear model +- [Distributions.jl](https://github.com/JuliaStats/Distributions.jl) for stat distributions