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(13 reviews)
Author: Graham Williams
ISBN : 1441998896
New from $43.78
Format: PDF
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Data Mining and Anlaytics are the foundation technologies for the new knowledge based world where we build models from data and databases to understand and explore our world. Data mining can improve our business, improve our government, and improve our life and with the right tools, any one can begin to explore this new technology, on the path to becoming a data mining professional. This book aims to get you into data mining quickly. Load some data (e.g., from a database) into the Rattle toolkit and within minutes you will have the data visualised and some models built. This is the first step in a journey to data mining and analytics. The book encourages the concept of programming by example and programming with data - more than just pushing data through tools, but learning to live and breathe the data, and sharing the experience so others can copy and build on what has gone before. It is accessible to many readers and not necessarily just those with strong backgrounds in computer science or statistics. Details of some of the more popular algorithms for data mining are very simply and, more importantly, clearly explained. Technology for transforming a database through data mining and machine learning into knowledge is now readily accessible.
Direct download links available for Free Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!) [Paperback]
- Series: Use R!
- Paperback: 394 pages
- Publisher: Springer; 2011 edition (February 25, 2011)
- Language: English
- ISBN-10: 1441998896
- ISBN-13: 978-1441998897
- Product Dimensions: 0.9 x 6 x 9 inches
- Shipping Weight: 1.7 pounds (View shipping rates and policies)
Free Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery
I am so happy I decided to buy this book. From the first page it is clear the author writes in excellent, approachable style -- there is no single place where I could find the author shows off his knowledge, nope, Graham Williams really teaches so the reader could understand. He allows to make friends with data mining in painless way; I appreciate the fact the first approach to each technique is done via GUI frontend (Rattle), but then the internals of R are explained -- the name of the package is given, how Rattle calls this or that function behind the scene, and also how to interpret the outcome, so in the end it is not only about the clicking with mouse.
I find this book very valuable for two reasons -- the comfort it provides (scientific book, and you want to read more and more), and it helps you focus on modeling the data, tweaking, etc (big plus for emphasis on training, validation and testing the models). However it is introductory book (I just can wish every introductory book was so informative and friendly). It is not related to the topic of data mining, but I noticed with pleasure the clear voice for open implementations of algorithms -- I can only concur that public reviews and collaboration allow to move things forward in faster pace.
If you would like to learn by example what the data mining is, how to apply, compare various algorithms this is the book for you. If you already know that and you would like to translate your knowledge to R, to some degree I would also recommend this book. This is not a book for learning R per se, so if you don't know the R it won't teach you that (rather make you a bit familiar), but don't worry, you can stick with GUI.
The book is not perfect though.
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