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tndoan
77b120bea6 Update Chap 09: (i) simplify the plot_svc function by using levels and colorbar_entry options of contour; and (ii) turn off useless output 2021-01-10 10:02:07 -05:00
tndoan
05a8375003 add blog post to Readme 2021-01-10 10:00:33 -05:00
tndoan
b15ed5f7b4 fix the figure 2020-12-16 09:49:11 -05:00
tndoan
581575d246 update according to comment of /u/EarthGoddessDude in Reddit 2020-12-15 16:08:56 -05:00
tndoan
d7e8db55bd update Readme 2020-12-13 20:32:34 -05:00
tndoan
e45b91bec6 Chapter 7 + 8 2020-12-11 14:41:15 -05:00
tndoan
abb90ab9f1 Chapter 5 + 6 2020-12-10 09:52:57 -05:00
tndoan
ac373ccfe7 Chapter 4 2020-12-10 09:48:58 -05:00
tndoan
309da44032 Chapter 3 2020-12-09 18:43:12 -05:00
tndoan
f7d6f61264 Chapter 10 2020-12-09 18:42:51 -05:00
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@@ -1,7 +1,7 @@
# ISL # Introduction to Statistical Learning with Julia
## Introduction ## 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. [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. The associated code is [R](https://www.r-project.org/about.html) 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](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 of this book in [Julialang](https://julialang.org/). 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 ## Library
@@ -14,3 +14,7 @@ In this project, I use Julia v1.5.1 and the following library
- [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) for data frame - [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) for data frame
- [GLM.jl](https://github.com/JuliaStats/GLM.jl) for generalized linear model - [GLM.jl](https://github.com/JuliaStats/GLM.jl) for generalized linear model
- [Distributions.jl](https://github.com/JuliaStats/Distributions.jl) for stat distributions - [Distributions.jl](https://github.com/JuliaStats/Distributions.jl) for stat distributions
## Note
I write a [blog post](http://tndoan.com/2020/12/25/lessons-learned-from-islr/) to summarize the lessons that I learn after doing this project.