Last update: Fri, 21 Oct 2022 11:41:38 +0000
This collection of tutorials is made for the statistics support center at Jacobs University. See the repo here. If you find any mistake or want to contribute, you are very welcome to open up an issue and point it out : )
I will be updating on a weekly basis.
RMySQL An interface between MySQL and R.
[Simple Linear Regression I] (https://angerhang.shinyapps.io/linearR/)
[Simple Linear Regression II] (/statsWithR/tutorials/linearR_2.html)
[Statistical Testing] (/statsWithR/tutorials/statsTests.html)
[ANOVA] (/statsWithR/tutorials/anova.html)
Part of my job at stats support is to explore the R packages that are related to text mining so here we go:
Text mining overview A brief introduction on what can we do with R for text mining tasks.
Introduction to text mining package
We dive into the text mining infrastructure of text mining in R and
have a focus on the use of package tm.
Introduction to TwitteR A fun package that gives us access to Twitter’s web API. We will do a naive analysis on Donald Trump’s popularity in the end.
Webmining Use tm.plugin.webmining package to retrieve feeds from the web.
RText A package that contains 9 common supervised learnings such as SVM and neural network as a start-to-product tool. Great for prototyping and experimenting.
I have also composed something for Rhadoop and SparkR last semester. If you are keen to big data. These might be a good start.