Free PDF KNIME Essentials, by Gábor Bakos
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KNIME Essentials, by Gábor Bakos
Free PDF KNIME Essentials, by Gábor Bakos
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About the Author
Gábor Bakos Gábor Bakos is a programmer and a mathematician, having a few years of experience with KNIME and KNIME node development (HiTS nodes and RapidMiner integration for KNIME). In Trinity College, Dublin, the author was helping a research group with his data analysis skills (also had the opportunity to improve those), and with the new KNIME node development. When he worked for the evopro Kft. or the Scriptum Informatika Zrt., he was also working on various data analysis software products. He currently works for his own company, Mind Eratosthenes Kft. (www.mind-era.com), where he develops the RapidMiner integration for KNIME (tech.knime.org/community/rapidminer-integration), among other things.
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Product details
Paperback: 148 pages
Publisher: Packt Publishing (October 16, 2013)
Language: English
ISBN-10: 1849699216
ISBN-13: 978-1849699211
Product Dimensions:
7.5 x 0.3 x 9.2 inches
Shipping Weight: 12.2 ounces (View shipping rates and policies)
Average Customer Review:
3.7 out of 5 stars
4 customer reviews
Amazon Best Sellers Rank:
#1,186,312 in Books (See Top 100 in Books)
it was ok, but I was expecting more. It was just about the basics. I don't even remember seeing anything about statistical analysis.
I was hoping to see more examples on how the icons can be used with appropriate explanations. I also thought that it is slightly over-priced.
good
I give this book three stars out of five.Let me briefly ouline my reasoning starting with whats's GOOD with "KNIME Essentials":The book presupposes experience in data analysis. No-nonsense therefore, No tedious lengthy explanations or unnecessary examples. Just straight dope.The book’s focus is on the data munging phase of a data analysis project – most central and important part of any data analysis project. Insights and useful tricks are aplenty.The book covers the essential preprocessing tasks and aptly describes how they are realized in KNIME. Reading the book gives you a solid foundation to build a data processing workflow with neat visualizations.However I want also to present some points where the book is LACKING:The reporting chapter felt a little off-track vis-à-vis the rest of the book.I couldn’t help but feel that the book’s rather sequential and orderly style stood in the way of both brevity and ambition to cover most of the KNIME’s preprocessing/exploration nodes. Perhaps it would have been more fitting to adopt a cookbook “Howto†format.The book has too many references to online guides and videos. It is not necessarily a bad thing. But: such style suits more for a series of blog posts, a full-fledged website or at the very least an e-pub file, read online with immediate emulation of topics discussed. That is how I did it, and I think it was a success; am not so sure that a paper version would have worked equally well.The book contains practically no details about specifically machine learning/scoring nodes or workflows. I found myself wanting to read more about KNIME’s data mining capabilities. After all, the homepage calls it a data mining tool and not an ETL one.It seems also that to build a data mining workflow adhering to CRISP-DM more work and knowledge (to be fetched elsewhere) is required; the book does not give you that.
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