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:
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!