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More Data Mining with Weka

Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more 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 Apr 24 (4 weeks ago)
Cost $89
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 Apr 24 (4 weeks ago)
Cost $89
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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