Introduction to Statistical Learning with Julia

Introduction

An Introduction to Statistical Learning: With Applications in R is a great book to learn data science. The associated code is R which is a nice programming language for statisticians. However, R is not fast and in my opinion, it does not have nice syntax. There is a project named ISLR-python which ports the book to Python. I was inspired by the Python project and try to implement the introduced materials of this book in Julialang. Julia is a new language which is faster and more friendly to scientific computing than Python. Hopefully, this code is helpful for Julia lovers when they read the book.

Library

In this project, I use Julia v1.5.1 and the following library

• Plots.jl for visualization
• CSV.jl for reading csv file
• Clustering.jl for clustering algorithms
• LIBSVM.jl for LibSVM implementation
• StatsPlots.jl for plotting statistic
• DataFrames.jl for data frame
• GLM.jl for generalized linear model
• Distributions.jl for stat distributions

Note

I write a blog post to summarize the lessons that I learn after doing this project.