Update Chap 09: (i) simplify the plot_svc function by using levels and colorbar_entry options of contour; and (ii) turn off useless output

add blog post to Readme
fix the figure
2021-01-10 10:02:07 -05:00 · 2021-01-10 10:00:33 -05:00 · 2020-12-16 09:49:11 -05:00 · 2020-12-15 16:08:56 -05:00 · 2020-12-13 20:32:34 -05:00 · 2020-12-11 14:41:15 -05:00
10 changed files with 72459 additions and 34334 deletions
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--- a/Chapter_03.ipynb
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--- a/Chapter_04.ipynb
+++ b/Chapter_04.ipynb
--- a/Chapter_05.ipynb
+++ b/Chapter_05.ipynb
--- a/Chapter_06.ipynb
+++ b/Chapter_06.ipynb
--- a/Chapter_07.ipynb
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--- a/Chapter_08.ipynb
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--- a/Chapter_09.ipynb
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--- a/Chapter_10.ipynb
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--- a/README.md
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@@ -1,7 +1,7 @@
-# ISL
+# Introduction to Statistical Learning with Julia

 ## 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

@@ -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 
 - [GLM.jl](https://github.com/JuliaStats/GLM.jl) for generalized linear model
 - [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.
Author	SHA1	Message	Date
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