-
Recent Posts
Recent Comments
Archives
- March 2020
- December 2018
- November 2017
- October 2017
- June 2017
- May 2017
- April 2017
- September 2016
- August 2016
- August 2015
- July 2015
- May 2015
- April 2015
- February 2015
- December 2014
- November 2014
- October 2014
- September 2014
- July 2014
- May 2014
- December 2013
- August 2013
- July 2013
- April 2013
- March 2013
- January 2013
- October 2012
- September 2012
- August 2012
- July 2012
- June 2012
- May 2012
- April 2012
- March 2012
- December 2011
- November 2011
- October 2011
- September 2011
- August 2011
- May 2011
- April 2011
Categories
Meta
Tag Archives: R
Coronavirus data analysis with R, tidyverse and ggplot2
Coronavirus data analysis – an analysis of data around the Novel Coronavirus (COVID-19) with R, tidyverse and ggplot2. Download full analysis reports at links below. Coronavirus data analysis – world wide http://www.rdatamining.com/docs/Coronavirus-data-analysis-world.pdf Coronavirus data analysis – China http://www.rdatamining.com/docs/Coronavirus-data-analysis-china.pdf
An 8-hour course on R and Data Mining
I will run an 8-hour course on R and Data Mining at Black Mountain, CSIRO, Australia on 10 & 13 December 2018. The course materials, incl. slides, R scripts and datasets, are available at http://www.rdatamining.com/training/course. Below is outline of the … Continue reading
Short Course on R and Data Mining, University of Canberra, Fri 7 Oct 2016
Short Course on R and Data Mining Information Technology and Engineering, University of Canberra Fees: There is no fees for the short course but seats are limited to 60 – so register early through http://www.meetup.com/CanberraDataSci/events/234168862/ Presenters: Dr Yanchang Zhao (Adjunct … Continue reading
Posted in Data Mining, R, text mining
Tagged Data Mining, R, R programming, text mining
Leave a comment
www2.rdatamining.com: a mirror site of RDataMining.com for Chinese users
RDataMining.com now has a mirror website at http://www2.rdatamining.com. Users in China can download RDataMining documents, code and data at above mirror site, if no access to http://www.rdatamining.com. Note that RDataMining.com will still be the primary site and please visit www2.RDataMining.com … Continue reading
R and Data Mining workshop at Deakin University
I will run a workshop on R and Data Mining for students in the Master of Business Analytics course at Deakin University in Melbourne on Thursday 28 May. The workshop will cover: – Introduction to Data Mining with R and … Continue reading
Free online data mining and machine learning courses by Stanford University
by Yanchang Zhao, RDataMining.com Three free online data mining and machine learning courses lectured by professors at Stanford University started in past two weeks, which provide excellent opportunities to learn advanced data mining and machine learning techniques. If you are … Continue reading
Recordings of RStudio Webinar Series on Essential Tools for Data Science with R
by Yanchang Zhao, RDataMining.com RStudio recently ran a series of live webinars on Essential Tools for Data Science with R, but it is inconvenient for people from other time zones to attend. Fortunately, the recordings have been made available online, … Continue reading
R and Data Mining – Examples and Case Studies now in Chinese
My book titled R and Data Mining – Examples and Case Studies now has its Chinese version, translated by researchers at South China University of Technology, and published by China Machine Press in September 2014. It is sold in China … Continue reading
R and Data Mining Workshop at AusDM 2014, Brisbane, 27 November
R and Data Mining Workshop at AusDM 2014 http://ausdm14.ausdm.org/workshop There will be a half-day workshop on R and Data Mining at the AusDM 2014 conference in Brisbane, Thursday afternoon, 27 November. The workshop will be composed of several sessions on … Continue reading
Free Stanford online course on Statistical Learning (with R) starting on 19 Jan 2015
This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and … Continue reading