This course introduces advanced data mining skills, following on from Data Mining with Weka. You’ll process a dataset with 10 million instances. You’ll mine a 250,000-word text dataset. You’ll analyze a supermarket dataset representing 5000 shopping baskets. You’ll learn about filters for preprocessing data, selecting attributes, classification, clustering, association rules, cost-sensitive evaluation. You’ll meet learning curves and automatically optimize learning parameters. Weka originated at the University of Waikato in NZ, and Ian Witten has authored a leading book on data mining.
This course is aimed at anyone who deals in data. It follows on from Data Mining with Weka, and you should have completed that first (or have otherwise acquired a rudimentary knowledge of Weka). As with the previous course, it involves no computer programming, although you need some experience with using computers for everyday tasks. High-school maths is more than enough; some elementary statistics concepts (means and variances) are assumed.
Before the course starts, download the free Weka software. It runs on any computer, under Windows, Linux, or Mac. It has been downloaded millions of times and is being used all around the world.
(Note: Depending on your computer and system version, you may need admin access to install Weka.)
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