Monday, 26 May 2014

Class 5 is now available

The lessons for Class 5, the last in our course, are now available on the course website:

https://weka.waikato.ac.nz/moredataminingwithweka

The 6 lessons in Class 5 addresses some important miscellaneous issues. Two are devoted to neural networks, both the simple Perceptron and multilayer Perceptrons — sometimes called “connectionist” models. Then we consider that perennial question, “how much data is enough?”, and show how to answer it using learning curves. Next we look at how to optimise the parameters of learning algorithms, and finally we return to the very beginning and re-visit the ARFF format, including some useful features that haven’t yet been encountered.

The post-course assessment opens on 28th May. Everything will remain open until 11th June, when the course will be closed. The videos, slides and transcripts will remain available at YouTube, Youku and the "Materials" site:


 http://www.cs.waikato.ac.nz/ml/weka/mooc/moredataminingwithweka/

We will also ask you to complete a survey for your opinions of the MOOC.

We are planning to run the introductory course “Data Mining with Weka” again in July. We will run “More Data Mining with Weka” again, but are not sure when: it depends on when we have sufficient new graduates from the introductory course to make it worthwhile. As for a possible third course, “Advanced Data Mining with Weka”, that’s still under consideration: there’s no schedule yet.


Please keep up the help on the course forum -- we greatly value your assistance.

cheers, and enjoy the remainder of the course!


Ian

1 comment:

  1. Hi,

    Thanks for an excellent course. I am now enlightened by the power of the WEKA ! :)

    In all seriousness, I very much enjoyed your course and teaching style. I now plan to use Weka in many data analysis projects.

    I also use R quite extensively and I was wondering about the best way to use Weka within R. I heard about the RWeka package. Perhaps you can comment? My objective is to develop adaptive algorithms and manipulate data sets in R, then call Weka from R for model building and predictions in an iterative way.

    Finally, I am definitely interested in a course on advanced data mining with Weka. Definitely sign me up if and when you plan to offer it !

    Thanks again for an excellent course!

    ReplyDelete