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More Data Mining with Weka

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. You can use the hashtag #FLmoredatamining to talk about this course on social media.

Topics Covered
  • Running large-scale data mining experiments
  • Constructing and executing knowledge flows
  • Processing very large datasets
  • Analyzing collections of textual documents
  • Mining association rules
  • Preprocessing data using a range of filters
  • Automatic methods of attribute selection
  • Clustering data
  • Taking account of different decision costs
  • Producing learning curves
  • Optimizing learning parameters in data mining

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The University of Waikato

Rating Not enough ratings
Length 5 weeks
Effort 4 hours per week
Starts Mar 11 (last week)
Cost $84
From The University of Waikato via FutureLearn
Instructors Ian Witten, Peter Reutemann, Jemma König, Eibe Frank
Download Videos Only via web browser
Language English
Subjects Programming
Tags C Tech & Coding

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FutureLearn

&

The University of Waikato

Rating Not enough ratings
Length 5 weeks
Effort 4 hours per week
Starts Mar 11 (last week)
Cost $84
From The University of Waikato via FutureLearn
Instructors Ian Witten, Peter Reutemann, Jemma König, Eibe Frank
Download Videos Only via web browser
Language English
Subjects Programming
Tags C Tech & Coding

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