### Resource News

#### RDataMining Tutorial on Machine Learning with R

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
- Association Rule Mining with R
- Text Mining with R
- Social Network Analysis with R
All materials of the above tutorial, incl. PDF slides, datasets and R scripts can be downloaded as a single ZIP archive at http://www.rdatamining.com/training/medascin/MLwR.zip
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 http://www.rdatamining.com/training/medascin |

#### Slides of CanberraDataSci seminars

Slides of 10+ seminars organised by Canberra Data Scientists Meetup Group are available on Google Drive. |

#### Slides on Text Mining with R

Download my latest slides on Text Mining with R at http://www.rdatamining.com/training/medascin/RDM-slides-text-mining-with-r.pdf, which is for a tutorial at the Melbourne Data Science Week, 1 June 2017. R script for the slides is available at http://www.rdatamining.com/training/medascin/RDM-scripts.zip. |

#### Slides on Association Rule Mining with R

Download my latest slides on Association Rule Mining with R at http://www.rdatamining.com/training/medascin/RDM-slides-association-rule-mining-with-r.pdf, which is for a tutorial at the Melbourne Data Science Week, 1 June 2017. |

#### An online textbook on Deep Learning

An online textbook on Deep Learning URL: http://www.deeplearningbook.org/ Deep Learning, a textbook by Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT press The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. |

#### Materials for the AusDM'16 tutorial on deep learning

#### SparkR: Scaling R Programs with Spark

SparkR: Scaling R Programs with Spark, a paper published at SIGMOD 2016. Download it at https://amplab.cs.berkeley.edu/publication/sparkr-scaling-r-programs-with-spark/ |

#### Using Natural Language Processing on Non-Textual Data with MLlib

Using Natural Language Processing on Non-Textual Data with MLlib, a presentation at Hadoop Summit 2016 in Melbourne https://github.com/cestella/presentations/blob/master/NLP_on_non_textual_data/src/main/presentation/NLP_on_non_textual_data.pdf |