The six lessons for Class 2 are now available on the course website:
https://weka.waikato.ac.nz/advanceddataminingwithweka
The mid-course assessment, which covers the material up to and including Class 2, is also available. Following that, there are 3 weeks to go (classes 3, 4 and 5).
The mid-course assessment will remain open for the rest of the course; the final assessment will appear during week 5.
The activities are a crucial part of the course: they're where most people will do their actual learning! However, they do not form part of the assessment, so don't be scared to get wrong answers. Also, some of the activities are pretty difficult and time-consuming. You don't necessarily need to actually complete them if you find that difficult on your computer, but you do need to understand what it is that you are supposed to do -- and why.
"Advanced Data Mining with Weka" has been designed so that participants at many different levels can learn as much as possible – and complete the course successfully. All you must do to get the Statement of Completion are the mid-course and final assessments -- which you can try as often as you like.
This class is about data stream mining, and MOA, Weka's big sister. MOA's algorithms are stream-oriented: they don't keep the dataset in main memory. You can access the algorithms from the Weka interface. But an important aspect of stream-oriented data mining is evaluation: how do you evaluate a learning algorithm that runs continuously on a data stream (which may, in addition, be evolving)? That is what the MOA interface is for, and you will learn about that too.
The Application in Lesson 2.6 is about applying Weka to a problem in bioinformatics, which is a very popular -- and important! -- area for data mining.
https://weka.waikato.ac.nz/advanceddataminingwithweka
The mid-course assessment, which covers the material up to and including Class 2, is also available. Following that, there are 3 weeks to go (classes 3, 4 and 5).
The mid-course assessment will remain open for the rest of the course; the final assessment will appear during week 5.
The activities are a crucial part of the course: they're where most people will do their actual learning! However, they do not form part of the assessment, so don't be scared to get wrong answers. Also, some of the activities are pretty difficult and time-consuming. You don't necessarily need to actually complete them if you find that difficult on your computer, but you do need to understand what it is that you are supposed to do -- and why.
"Advanced Data Mining with Weka" has been designed so that participants at many different levels can learn as much as possible – and complete the course successfully. All you must do to get the Statement of Completion are the mid-course and final assessments -- which you can try as often as you like.
This class is about data stream mining, and MOA, Weka's big sister. MOA's algorithms are stream-oriented: they don't keep the dataset in main memory. You can access the algorithms from the Weka interface. But an important aspect of stream-oriented data mining is evaluation: how do you evaluate a learning algorithm that runs continuously on a data stream (which may, in addition, be evolving)? That is what the MOA interface is for, and you will learn about that too.
The Application in Lesson 2.6 is about applying Weka to a problem in bioinformatics, which is a very popular -- and important! -- area for data mining.
cheers, and keep going!
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