The six lessons for Class 3 are now available on the course website:
https://weka.waikato.ac.nz/advanceddataminingwithweka
After this week there are 2 weeks to go (classes 4 and 5).
The mid-course assessment is also now available. Do it when you have finished Class 2 (although it will remain open for the rest of the course). The final assessment will appear during week 5.
https://weka.waikato.ac.nz/advanceddataminingwithweka
After this week there are 2 weeks to go (classes 4 and 5).
The mid-course assessment is also now available. Do it when you have finished Class 2 (although it will remain open for the rest of the course). The final assessment will appear during week 5.
Check your Profile to
ensure that your assessment marks have been recorded correctly. Also,
check that the name in your Profile is the one you want on your Statement of Completion: as we will use that exact text for the Statements.
Our goal is to enable you to learn as much as possible from this course, and we recognize that doing the assessments may not be a priority for you. However, our ability to mount follow-up MOOCs will depend on the success of this one as perceived by my University -- and the number of people who complete it successfully will be a key metric. Thus I urge you to do the assessments for my sake, if not your own :-)
In this class we'll learn about interfacing to other data mining packages. The first lesson shows you how to access LibSVM and LibLINEAR, and the remaining ones show you how to access some of the many facilities in the popular R statistical computing package. These increase the scope of Weka enormously!
The Application lesson 3.6 shows you how to use Weka to analyze functional MRI Neuroimaging data, and in the Activity you will actually do some of this analysis!
cheers, and keep going!
Our goal is to enable you to learn as much as possible from this course, and we recognize that doing the assessments may not be a priority for you. However, our ability to mount follow-up MOOCs will depend on the success of this one as perceived by my University -- and the number of people who complete it successfully will be a key metric. Thus I urge you to do the assessments for my sake, if not your own :-)
In this class we'll learn about interfacing to other data mining packages. The first lesson shows you how to access LibSVM and LibLINEAR, and the remaining ones show you how to access some of the many facilities in the popular R statistical computing package. These increase the scope of Weka enormously!
The Application lesson 3.6 shows you how to use Weka to analyze functional MRI Neuroimaging data, and in the Activity you will actually do some of this analysis!
cheers, and keep going!
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