Blog Archives

Call for participation: AusDM 2014, Brisbane, 27-28 November

October 25, 2014
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Call for participation: AusDM 2014, Brisbane, 27-28 November

********************************************************* 12th Australasian Data Mining Conference (AusDM 2014) Brisbane, Australia 27-28 November 2014 http://ausdm14.ausdm.org/ ********************************************************* The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. Since AusDM’02 the conference … Continue reading →

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My visits and RDataMining talks in North America

October 11, 2014
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My visits and RDataMining talks in North America

  I visited Mexico recently and is now travelling in US. In the 1st week of October, I delivered a keynote talk at the CONAIS 2014 conference in Mexico, as well as a one-day workshop on data mining with R … Continue reading →

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RDataMining Slides Series

September 14, 2014
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RDataMining Slides Series

by Yanchang Zhao, RDataMining.com I have made a series of slides on R and data mining, based on my book titled R and Data Mining — Examples and Case Studies. The slides will be used at my presentations at seminars … Continue reading →

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Slides of 12 tutorials at ACM SIGKDD 2014

September 7, 2014
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Slides of 12 tutorials at ACM SIGKDD 2014

Slides of 12 tutorials taught by data science experts and thought leaders at ACM SIGKDD 2014 are provided at http://www.kdd.org/kdd2014/tutorials.html. Below is a list of them. 1.Scaling Up Deep Learning Yoshua Bengio 2. Constructing and mining web-scale knowledge graphs Antoine … Continue reading →

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RDataMining group having 6000 members today

July 5, 2014
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RDataMining group having 6000 members today

RDataMining Group: http://group.rdatamining.com Twitter: @RDataMining Website: http://www.RDataMining.com The RDataMining group has 6000 members today, 5 July 2014. Created in August 2011, this group has developed into a big community with 6000 member within three years. Since its creation, many members … Continue reading →

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Currency Exchange Rate Forecasting with ARIMA and STL

July 3, 2014
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Currency Exchange Rate Forecasting with ARIMA and STL

I have made an example of time series forecasting with R, demonstrating currency exchange rate forecasting with the ARIMA and STL models. The example is easy to understand and follow. R source files are provided to run the example. The … Continue reading →

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Step-by-Step Guide to Setting Up an R-Hadoop System

May 30, 2014
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Step-by-Step Guide to Setting Up an R-Hadoop System

by Yanchang Zhao RDataMining.com Following my first R-Hadoop system setup guide written in Sept 2013, I have further tested setting up a Hadoop system for running R code, as well as using HBase. I have tested it both on a … Continue reading →

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A Sequence of 9 Courses on Data Science Starts on Coursera on 2 June and 7 July 2014

May 26, 2014
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A Sequence of 9 Courses on Data Science Starts on Coursera on 2 June and 7 July 2014

A sequence of 9 courses on Data Science will start on Coursera on 2 June and 7 July 2014, to be lectured by(Associate/Assistant) Professors of Johns Hopkins University. The courses are designed for students to learn to become Data Scientists … Continue reading →

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A Coursera course on Machine Learning starts on 16 June

May 21, 2014
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A Coursera course on Machine Learning starts on 16 June

A 10-week course on Machine Learning by Andrew Ng from Stanford University will start on Coursera on 16 June. Below are descriptions of the course picked up from Coursera. The course provides a broad introduction to machine learning, data mining, … Continue reading →

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CFP: AusDM 2014 – the 12th Australasian Data Mining Conference

May 13, 2014
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CFP: AusDM 2014 – the 12th Australasian Data Mining Conference

********************************************************* 12th Australasian Data Mining Conference (AusDM 2014) Brisbane, Australia 27-28 November 2014 http://ausdm14.ausdm.org/ ********************************************************* Data Mining is the art and science of intelligent analysis of (usually big) data sets for meaningful insights. Data mining is actively applied across all … Continue reading →

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