I have run a tutorial on Machine Learning with R for the Melbourne Data Science Week in June 2017, which consists of four sessions:
- R Programming:
basics of R language and programming, parallel computing, and data import and export
- Association Rule Mining with R:
mining and selecting interesting association rules, redundancy removal, and rule visualisation
- Text Mining with R:
text mining, word cloud, topic modelling, and sentiment analysis,
- Social Network Analysis with R:
graph construction, graph query, centrality measures, and graph visualisation
All materials of the above tutorial, incl. PDF slides, datasets and R scripts can be downloaded as a single ZIP archive at
How to use it:
- Decompress the ZIP archive, and you will find file and folders below:
- MLwR.Rproj: RStudio project file
- code: R scripts
- data: datasets
- docs: PDF slides
- figures: charts
- Open the “MLwR.Rproj” file with RStudio
- Open each PDF slides file (in folder “docs”) and run its corresponding R scripts (in folder “code”) to learn each topic
Detailed instructions for the tutorial are available at
See my latest slides on Association Rule Mining with R at
It is one of my tutorials on Machine Learning with R for the Melbourne Data Science Week on 1 June 2017. If you are interested, details can be found at
AusDM 2017 will be a special event this year being held in conjunction with IJCAI in Melbourne. This is a tremendous opportunity to present data mining research from Australia to a wider audience, with collaborative arrangements with IJCAI to invite wider participation.
Submissions are required by 5pm Monday 22 May 2017. Visit http://ausdm17.ausdm.org for details.
14th Australasian Data Mining Conference (AusDM 2016)
6-8 December 2016
Join us on LinkedIn: http://www.linkedin.com/groups/AusDM-4907891
The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. AusDM’16 seeks to showcase: Research Prototypes; Industry Case Studies; Practical Analytics Technology; and Research Student Projects.
Publication and topics
We are calling for papers, both research and applications, and from both academia and industry, for presentation at the conference. Accepted papers will be published in an up-coming volume (Data Mining and Analytics 2016) of the Conferences in Research and Practice in Information Technology (CRPIT) series by the Australian Computer Society which is also held in full-text on the ACM Digital Library. AusDM invites contributions addressing current research in data mining and knowledge discovery as well as experiences, novel applications and future challenges.
Submission of papers
– Academic submissions: Regular academic submissions can be made in Research Track reporting on research progress, with a paper length of between 8 and 12 pages in CRPIT style.
– Industry submissions: Submissions can be made in the Application Track to report on specific data mining implementations and experiences in governments and industry projects. Submissions in this category can be between 4 and 8 pages in CRPIT style.
– Industry Showcase submissions: Submission from industry and government on an analytics solution that has raised profits, reduced costs and/or achieved other important policy and/or business outcomes can be made in this track with a one page Abstract only.
Online submission system
Paper Submission: extended to 6pm, Friday 2 Sept 2016, Australian Eastern Standard Time (AEST)
Authors Notified: Monday 24 October 2016
Camera Ready Submission: Monday 7 November 2016
Conference Dates: 6-8 December 2016