Rapid - I

Open source software for big data analytics.
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Rapid-I. Report the Future.

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Documentation

	Book: Data Mining for the Masses In Data Mining for the Masses, professor Matt North—a former risk analyst and database developer for eBay.com—uses simple examples, clear explanations and free, powerful, easy-to-use software to teach you the basics of data mining; techniques that can help you answer some of your toughest business questions. RapidMiner is used as the data mining tool throughout the book. http://docs.rapid-i.com/r/data-mining-for-the-masses
	Manual RapidMiner 5.0+ The RapidMiner User Manual is the main documentation of RapidMiner containing an introduction into the basic concepts together with a complete description of the program itself. http://docs.rapid-i.com/r/rm-manual-en
	Manual RapidMiner 5.2+: Advanced Charts In addition to the user manual, this book describes the advanced RapidMiner charts in much detail. All features are described and illustrated with examples. http://docs.rapid-i.com/r/rm-charts-en
	RapidMiner Operator Reference With almost 1000 pages, this is the complete reference documentation of RapidMiner operators. It explains all parameters, ports, and subprocesses, and the usage of each operator is illustrated with at leach one tutorial process. http://docs.rapid-i.com/r/rm-reference-en

	RapidMiner Video Tutorials A collection of video tutorials shows how RapidMiner can be used to efficiently solve data mining problems. Topics cover user interface, data import and preparation, modelling, evaluation, and visualization. http://docs.rapid-i.com/r/rm-videos
	RapidAnalytics Video Tutorials This video series explains the usage of the RapidAnalytics data mining server. Topics include using RapidAnalytics as a repository, scheduling jobs, reporting, and the creation of Web services to integrate RapidAnalytics with other parts of your IT infrastructure. http://docs.rapid-i.com/r/ra-videos
	How to Extend RapidMiner This whitepaper helps you to get started with implementing your own RapidMiner Extensions. From implementing new algorithms to designing user interface components, this guide contains step by step explanations and is accompanied by a tutorial project which you can immediately run. http://docs.rapid-i.com/r/whitepaper-how-to-extend
	RapidMiner in Academic Use Using RapidMiner in academic projects and for teaching has a lot of advantages. This paper illustrates how you can use RapidMiner to perform data analyses in data driven sciences, evaluate newly developed data mining algorithms, and add a great amount of visibility and reproducibility to your results. http://docs.rapid-i.com/r/whitepaper-academia-en