1
Current Active Bookmarks
1.1
Action Items
1.2
Linear Algebra
1.3
key driver analysis
1.3.1
Continuous and automatic key driver analysis of customer feedback
1.4
Finalfit
1.4.1
Elegant regression results tables and plots in R: the finalfit package
1.4.2
Finalfit, knitr and R Markdown for quick results
1.5
Bookdown
1.5.1
bookdown: Authoring Books and Technical Documents with R Markdown
1.5.2
bookdownplus package
1.5.3
Writing your thesis with bookdown
1.5.4
How to Start a Bookdown Book
1.5.5
Mastering Software Development in R: Continuous Integration
1.5.6
Writing your thesis with bookdown
1.6
Git
1.6.1
Happy Git and GitHub for the useR
1.6.2
Learn Git Branching
1.6.3
getting-started-with-git-egit-eclipse
1.6.4
Github On Demand Training
1.6.5
Other Git
1.7
Other
2
My intro to R recommendations:
2.1
Read this “New to R” article:
2.2
Start by setting up R:
2.3
Spend some time learning the basics of Base R:
2.4
Follow that by learning the tidyverse:
2.5
As you go about learning R, think about your “R workflow”" (I recommend three articles):
3
Learning Resources
3.1
New to R Kickstart your learning and career with these 6 steps!
3.1.1
New to R Kickstart your learning and career with these 6 steps! – paulvanderlaken.com (Paul van der Laken, 2017)
3.2
R for Data Science
3.2.1
R for Data Science
3.2.2
R for Data Science Solutions
3.3
Other Learning Resources
3.4
Git
3.4.1
git ready: learn git one commit at a time
4
UC Berkeley MIDS program
4.1
Useful Links
4.2
Calculus materials:
4.3
Python:
4.4
Linear Algebra:
4.5
Other Statistics resources:
5
Meetup - East Bay R Language Beginners Group
5.1
Oakland Ford GoBikes - 2018-09-04
5.2
R Lightening Talks! Time Series, Classifier Interpretation, Reticulate Python - 2018-10-02
5.2.1
Jeff Newmiller
6
Meetup - USF
6.1
Analysing & Preventing Unconscious Bias in Machine Learning. Rachel Thomas - 2018-10-19
6.2
USF Intro session - 2018-10-19
6.3
Python & Other Stuff Links flagged on mobile that need to be integrated in blog
7
Bookmarks - Temp
7.1
R Links flagged on mobile that need to be integrated in blog
8
Bookmarks with Thought
8.1
R Reference
8.2
R Graphs
8.3
R NLP - Natural Language Processing
8.3.1
General / unassigned
8.3.2
R Sentiment Analysis
8.4
R Stats
8.5
R Markdown
8.6
R Workflow / Version Control
8.7
R Shiny
8.8
R Projects
8.9
R Blogs and general reference
8.10
R links/blog posts to read
8.11
R links/blog posts to read without annotation
8.12
R links iPhone that need to be integrated in blog
8.13
R links ipad that need to be integrated in blog
8.14
Python & Other links iPhone that need to be integrated in blog
9
Other Stuff
9.1
Python
9.1.1
Python & Other Stuff - Annotated
9.1.2
Python & Other Stuff - to read without annotation
9.1.3
Python - to read without annotation
9.1.4
Other Stuff - to read without annotation
9.2
Surveys
9.3
Fun
9.4
Six Sigma
9.5
CX related
9.6
Rmd stuff
10
Interview Skills
10.1
Pre-interview prep
10.1.1
Vocal warm-up exercises
10.2
Plan
10.3
References and links
10.3.1
Ted Talks
11
Playground
11.1
Building a Hacker News scraper with 8 lines of R code using rvest library
11.2
R Markdown
11.3
Including Plots
12
Test
References
13
Test
13.1
Test stuff
14
test n stuff
Ongoing blog of Conor’s path to R mastery
12
Test
test1 <-
1
+
1
test1
## [1] 2
2
Definition 12.1 (Pythagorean theorem)
For a right triangle, if
\(c\)
denotes the length of the hypotenuse and
\(a\)
and
\(b\)
denote the lengths of the other two sides, we have
\[a^2 + b^2 = c^2\]